business intelligence master thesis topics

For enquiries call:

+1-469-442-0620

Business intelligence and Visualization

How to Write a Perfect Research Paper?

Writing a perfect Business Intelligence research paper requires careful planning, organization, and attention to detail. Here is a step-by-step guide to help you write an excellent research paper:

Understand the Business Intelligence Thesis: Begin by thoroughly reading and understanding the requirements and guidelines provided by your instructor or institution. Clarify any doubts or questions before proceeding.

Ø Choose a topic: Select a research topic that is interesting, relevant, and has sufficient available resources for investigation. Refine your topic to make it focused and specific.
Conduct preliminary research: Before diving into writing, conduct preliminary research to familiarize yourself with the existing literature, theories, and findings related to your topic. This will help you develop a strong theoretical foundation for your research paper.
Develop a thesis statement: Craft a clear and concise thesis statement that outlines the main argument or objective of your research. The thesis statement should guide your entire paper and provide a roadmap for the reader.
Create an outline: Organize your thoughts and main points by creating a detailed outline for your research paper. This will help you structure your paper logically and ensure a coherent flow of ideas.
Gather and evaluate sources: Collect relevant sources, such as academic journals, books, reputable websites, and other scholarly materials. Evaluate the credibility, reliability, and relevance of each source to ensure that you use reliable information in your research paper.
Write the introduction: Start your paper with an engaging introduction that captures the reader's attention and provides background information on your topic. Clearly state your research objectives and the significance of your study.
Develop the literature review: Provide a comprehensive review of the existing literature on your topic. Summarize and critically analyse relevant studies, theories, and frameworks. Identify gaps or limitations in the literature that your research aims to address.
Methodology: Provide an overview of the research approach employed, encompassing the research design, methods for data collection, sample size determination, and the techniques used for data analysis. Justify your choices and explain how they align with your research objectives.
Present your findings: Present your research findings in a clear, organized, and logical manner. Use appropriate tables, charts, or graphs to illustrate data and support your arguments. Interpret the results and discuss their implications.
Discussion and conclusion: Analyze and interpret your findings in the context of your research objectives. Discuss the implications, limitations, and potential areas for future research. Summarize your main points and restate your thesis in the conclusion.
Revise and edit: Review your research paper for clarity, coherence, grammar, and punctuation errors. Revise and refine your content, ensuring that your arguments are well-supported, and your writing is concise and precise.
Proofread: Carefully proofread your paper to catch any spelling or typographical errors. Check formatting, citations, and references to ensure accuracy and consistency.
Seek feedback: Before finalizing your research paper, seek feedback from your peers, mentors, or professors. Incorporate their suggestions and make necessary revisions to enhance the quality of your paper.
Finalize and submit: Make the final adjustments and formatting changes, double-check all references, and ensure that your research paper meets the required guidelines. Submit your paper within the given deadline.
Writing a perfect research paper takes time, effort, and attention to detail. By adhering to these steps and adopting a systematic approach, it is possible to generate a research paper of exceptional quality that effectively communicates your findings and makes a significant contribution to your field of study.

Enroll in our dynamic ecba classes and unlock the key to success in business analysis. Level up your skills and advance your career today!

Why Business Intelligence is Important in 2024?

Business intelligence (BI) is increasingly recognized for its significance as organizations endeavour to make well-informed decisions in an intricate and fiercely competitive business environment. In the year 2024, BI holds immense value due to the following reasons: The prominence of data-driven decision-making: In the present era of digitization, enterprises possess an abundance of data resources.

Data-driven decision-making: In the digital age, BI helps businesses analyse vast data, gain actionable insights, and make informed decisions based on evidence and trends, reducing reliance on intuition.
Competitive advantage: BI provides organizations a competitive edge by extracting valuable insights from data, enabling quick responses to market trends, customer preferences, and emerging opportunities, optimizing operations, and capitalizing on market shifts.
Customer insights and personalization: BI enables organizations to gain a deeper understanding of their customers by analysing their behaviour, preferences, and feedback. Utilizing this information enables the customization of marketing campaigns, enhancement of customer experiences, and optimization of product offerings.
Forecasting and predictive analytics: Business Intelligence (BI) employs predictive modelling and forecasting by analyzing historical data and patterns to anticipate future trends and outcomes. This enables organizations to make proactive decisions, allocate resources effectively, and mitigate risks based on accurate predictions of market demand and customer behaviour.
Data governance and compliance: With the increasing focus on data privacy and security, BI tools play a vital role in ensuring data governance and compliance with regulatory requirements. They manage data access, monitor data quality, and enforce data protection measures.

By leveraging BI effectively, businesses can stay agile, adapt to changing market conditions, and drive sustainable growth in a data-centric world. You can go through this well-designed course to learn more about KnowledgeHut Business Intelligence and Visualization training .

In conclusion, writing a perfect research paper requires meticulous planning, organization, and attention to detail. By adopting a systematic approach and adhering to the provided guidelines, you will be able to create a research paper of outstanding quality that effectively communicates your findings and makes a valuable contribution to your field of study.

Throughout the research paper writing process, it is crucial to have a clear understanding of the assignment and choose a relevant and engaging topic. Conducting preliminary research helps in developing a strong theoretical foundation and crafting a focused thesis statement. Creating a detailed outline ensures a logical structure and coherent flow of ideas in the paper.

The gathering and evaluation of credible sources are essential for supporting your arguments and providing a comprehensive literature review. Careful consideration of research methodology, data collection methods, and analysis techniques helps in ensuring the validity and reliability of your findings.

The presentation of your findings should be clear, organized, and supported by appropriate visuals. The goal of business intelligence is to transform raw data into actionable insights that can drive strategic and operational decisions. Power BI is the most trending tool these days and we do not want to stay behind in the race to get ahead in knowing about BI tools, so check out this amazing Power BI course which will help you upskill yourself and learn a lot more about Business Intelligence.

Frequently Asked Questions (FAQs)

BI research explores data techniques and tools for informed decision-making in organizations, covering data analytics, visualization, mining, machine learning, and predictive modeling to boost business performance.

Three major types of business intelligence:

Descriptive BI: Analyses historical data to gain insights into past events within the organization.
Predictive BI: Uses statistical models to forecast future trends and outcomes based on historical data.
Prescriptive BI: Recommends actions or strategies by going beyond descriptive and predictive analytics.

The four fundamental concepts of business intelligence are data collection from diverse sources, data analysis using statistical techniques and machine learning, data visualization with charts and graphs for easy comprehension, and data-driven decision-making to support organizational performance and achieve business objectives.

Gauri Guglani

Gauri Guglani works as a Data Analyst at Deloitte Consulting. She has done her major in Information Technology and holds great interest in the field of data science. She owns her technical skills as well as managerial skills and also is great at communicating. Since her undergraduate, Gauri has developed a profound interest in writing content and sharing her knowledge through the manual means of blog/article writing. She loves writing on topics affiliated with Statistics, Python Libraries, Machine Learning, Natural Language processes, and many more.

Avail your free 1:1 mentorship session.

Something went wrong

Upcoming BI & Visualization Batches & Dates

prive academy

Tips on thesis defense presentation
Writing a dissertation in informatics
20 topics for a perfect dissertation
Tricks for inventing great topics
20 topics on job satisfaction
Social science ideas
Health law topics
Multiculturalism
Business intelligence
MBA thesis topics
Expert writing help
Finding a great writing service
Tips on thesis defense slideshow
Getting motivated for writing
Using a PhD thesis database
Finding a reliable thesis writing service
Benefits of using a thesis database
Nuclear physics writing help
Advice for perfect formatting
How to buy thesis for cheap
Writers to do my thesis
Getting a thesis appendix sample
Finding a decent introduction example
Writing an introduction in business
Picking a dissertation research strategy
Crafting a thesis proposal cover page
Getting thesis writing help online
Finding great samples on the web
How to get a quality writing sample
Writing a dissertation proposal
Who can help to write my dissertation?
Selecting a dissertation writing service
How to plan my writing?
Finding a thesis proposal example
Free graduate theses
Writing assistance
SIGN IN / SIGN UP

MBA Dissertation Topics On Business Intelligence: 20 Best Ideas

Writing a dissertation on business intelligence is a major challenge for many MBA students. You need to choose a decent topic idea to make your research interesting and valuable. So, get started as soon as you get the assignment. The following guidelines and examples are designed to make this difficult task a bit easier for you.

Hints for Finding a Good Dissertation Topic for MBA Level

Discuss your ideas with your professor and follow the guidance on generating, outlining, and finalizing your topic.
Base your research in a real world of your study area, e.g. study business and management practices, investigate current issues, etc.
Choose something that you feel comfortable and confident writing about, consider prompts that arouse your curiosity.
Ensure that you’re knowledgeable about your subject, and it can be helpful for your future career.
Avoid dissertation topics which are too complicated for you to research and write about; don’t aim to surprise your instructor.
Consider an issue that you discussed in class, learn more about it, and come up with a perspective solution.
Revise your textbook, class reading, and notes to think of something worth further exploration.

Top MBA Dissertation Prompts on Business Intelligence

Creating a healthy business environment: data sharing issues.
Time for changes: business intelligence innovations in the 21st century.
Online data storage for enterprises: the effectiveness and ways for improvement.
Meeting the company’s information requirements: useful strategies and possible complications.
Using data discovery tools: the key advantages and disadvantages.
Mobile business intelligence: the current state and development perspectives in different countries.
Business data management: a comparison of different solutions.
Using customer profiles: the core strategies for businesses regarding market share increase.
The importance of market research for start-up companies.
Applying high-cost analytic software: the main benefits.
Ensuring the safety of data and information: security measures practiced by international companies.
The ethical aspects of data sharing in the company’s environment: a case study of a particular organization.
The issues related to large amounts of data accumulated throughout the decades.
Supporting innovations in business intelligence: effective strategies.
Improving the relationship between staff and clients: best practices of using various data.
The most important functions of business intelligence.
Optimization of key performance indicators: best practices in the developed countries.
How much data in enough: the role of records amount and quality in business intelligence implementation.
The vital features for a BI portal and a web portal in general: a comparison study.
Problems that companies face with unstructured and semi-structured data.

75 Business Intelligence Essay Topic Ideas & Examples

🏆 best business intelligence topic ideas & essay examples, ⭐ good research topics about business intelligence, 👍 simple & easy business intelligence essay titles.

Business Intelligence and Decision Making As can be deduced from the preceding discussion, both the IBM and SAS Business Intelligence solutions have a variety of benefits to offer to business enterprises.
Application of Artificial Intelligence in Business The connection of AI and the business strategy of an organization is displayed through the ability to use its algorithm for achieving competitive advantage and maintaining it.
Kinds of Big Data: Foundations of Business Intelligence IBM and the British Library collaborated to build a big data system. The Library collects large volumes of unorganized Web data to make them extracted, annotated, and graphically analyzed with the aid of IBM BigSheets.
Application of Business Intelligence Solutions in Budgeting While the materials focused more on the practical application of budgeting knowledge in explaining the process of budget preparation, I wanted to learn more about the planning aspect of budgeting. It was interesting to gain […]
What Is Business Intelligence? The process allows managers, executives, and other business leaders to generate effective and accurate company choices or decisions faster or quicker to deliver better outcomes in the required time.
Decision Support System, Business Intelligence and Examples of Analytics It serves to gather and analyze large amounts of data to expand the capabilities but not to replace the course of the initial decision.
Business Intelligence Project: Using Predictive Analytics to Improve a Business Overall, the study aims to investigate the impact of predictive analytics by assessing inventory, sales, and customer data of a small business.
CGR Company: Business Intelligence Business intelligence is a notion that is used by the software vendors and IT consultants to describe the infrastructure for warehousing.
Business Intelligence Systems: Coronavirus Disease The findings reveal that the coronavirus stimulates individuals and businesses to mobilize their efforts to overcome the existing challenges in the spheres of business innovation and entrepreneurship.
Business Intelligence System in the Jefferson Medical Centre The increase in competition in the business environment has mandated business organizations many business organizations to initiate a policy of Business Intelligence system into their business strategic decision to enhance business competitive advantages.
WidgetSupplies Business Intelligence Requirements WidgetSupplies’ business needed a simple system to easily record sales and to compare the projected sales and the actual which the system could not provide. In a nutshell, it is important to acknowledge that as […]
The Importance of Business Intelligence Industry Creative agility on the part of Procter and Gamble will be critical to the launch of the new product and this includes creativity in promotion and advertising, reaching the target consumers, packaging, outwitting the competitors, […]
Significance of Business Intelligence This use of the term BI reached its height of popularity, as measured in a number of publications and studies, during the 1970s when it was viewed as an effective new way for organizations to […]
Building Business Intelligence Using SAS The respondents were chosen to provide an answer on the questionnaire; the results of the answers are the following: It is evident that the system used by Traffic Department should keep pace with the progress […]
Business Intelligence Strategy: Online Music Store Every day I had to get up in the early hours of the night to log on to http://www.billboard.com/charts/hot-100 to be able to see which new songs have come into the chart and know how […]
Intelligence and Communication in Business Settings Consequently, in an attempt to retain efficient and effective communication, the communicator’s substantial knowledge of the language, as learning styles, largely aid in creating awareness of the need to select words precisely during communication.
Saudi Arabian Companies: Business Intelligence System These people must be able to make recommendations about the functionality of the BI system and its design. They can rely on the experience of other companies, which tried to implement BI system, and avoid […]
Business Intelligence in Healthcare The given essay discusses the current benefits of BI and possible breakthroughs in preventative health, which may come about because of the use of such technologies. This may lead to the betterment of health management […]
Business Intelligence Strategy and Framework Most importantly, the BI strategy framework monitors the alignment of the corporate mission to the current business strategy that leads to resilience.
Business Intelligence: Create, Implement, Use The position taken on business intelligence is that BI is a process that is created, implemented and practiced using business analytic tools to analyze past and present data and enable effective decision making at all […]
Business Intelligence and Analytics The obvious benefit that the utilization of business intelligence and analytics can bring to an establishment is, as said, the improvement of decision-making.
The Use of Competitive Intelligence in Business The process directed at the acquisition and collection of the data concerning the advantages and disadvantages of a business and its competitors is referred to as competitive intelligence.
Decision Support System and Business Intelligence The inability of an organisation to prepare users adequately for the system change is the major cause of DSS/BI failures in many organisations.
Mobile Business Intelligence Trends The use of foresight theory and practices to identify future trends in business processes has allowed firms to adjust their business activities.
Business Intelligence Systems and Data Organization The hypothesis of the study is the following: the integration of the BI systems in the police working process impacts the data organization in a positive way; as a result, it may increase the working […]
The UAE Traffic Department’s Business Intelligence The primary purpose of the paper is to evaluate the effectiveness of the business intelligence for the Traffic Department of the United Arab Emirates.
E-Commerce: Mining Data for Better Business Intelligence The method allowed the use of Intel and an example to build the study and the literature on data mining for business intelligence to analyze the findings.
The Importance of Business Intelligence Intelligent decisions needs to be made to drive business forward thus the importance of business intelligence which is the computer based applications and technologies for gathering, storing and analyzing business data such as sales revenue […]
Cloud Business Intelligence in SMEs Cloud business Intelligence allows SMEs to enjoy the benefits of the process in a short amount of time. In the past, this involved all the expenses entailed in the purchase of the license for the […]
Current and Emerging Technology in Data Warehousing and Business Intelligence To help address this need, business have developed a desire for data warehousing tools that designed to offer flexibility in terms of decision making by the management and chief information officers.
Business Intelligence Solutions in UAE Companies An organization seeking the best intelligence vendors in the market should evaluate other business intelligence organizations on the bases of their BI vendors and should also seek the opinion of other successful BI enabled companies […]
Business Intelligence and Data Warehousing System The name business intelligence is a name that was formed in the mid 1950s to describe the act of changing un-grouped data from a company’s or an organization’s contrasting functional data into a common data […]
Various Concepts Used in Decision-Making in Business In addition to this, businesses and companies tend to use business intelligence to bring about consistency in decision making, emphasize on incorporation of business information and analytical technique into tactical decisions and strategic processes and […]
Business Intelligence Approaches Business intelligence is a term used to refer to a collection of applications that aim at keeping and making available a data bank in a certain industry or organization; the bank is referred to when […]
Strategic Management Using Business Intelligence Tools in Metallurgical Plants
Business Intelligence and Knowledge Management Differences
Customer Data Analysis Model Using Business Intelligence Tools in Telecommunication Companies
Supply Chain Issues and Business Intelligence Technologies
Business Intelligence and Data Science
Sustainable Knowledge Capability Through Business Intelligence Design
Improving Business Intelligence Traceability and Accountability: An Integrated Framework of Product and Meta Content Map
Business Intelligence Tools for Improve Sales and Profitability
Applying Business Intelligence Techniques to Businesses Using Google
Business Intelligence Management and Leadership
Increasing the Business Performances Using Business Intelligence
Mobile Business Intelligence: Allocation of Mobile Workers for Competitive Information Gathering
Big Data Analytics and Business Intelligence in Industry
Business Intelligence Support for Project Management
Decision Trees: Business Intelligence, Data Latency, and Data Mining
Business Intelligence and Enterprise Resource Planning
Knowledge Management, Business Intelligence, and Analytics
Optimizing Business Intelligence Results Through the Strategic Application of Software Process Model
Predictive Analytics: The Future of Business Intelligence
Big Data Mining and Business Intelligence Trends
Improving Customer Relationship Management Through Business Intelligence
Intelligent Analytics: Integrating Business Intelligence and Web Analytics
The Border Between Business Intelligence and Psychology: Segmentation Based on Customer Behavior
Business Intelligence, Accountant, and Marketing Intelligence
Managing Sustainability With Eco-Business Intelligence Instruments
Systems in Business Intelligence and Information Systems
Business Intelligence: Applications, Trends, and Strategies
Agile Development for Service-Oriented Business Intelligence Solutions
Success Factors for Business Intelligence System Implementation in Public Sector Organization
Business Intelligence, Retail Industry, and Multi-Market Competition
Best Practices When Offshoring Business Intelligence
Natural Intelligence Applications for Business Intelligence in Online and Catalog Retailing Firms
Methodological Aspects and Case Studies of Business Intelligence Application Tools in Knowledge Management as Corporation’s Strategy Development
Magic Quadrant for Business Intelligence and Analytics Platforms
Open Information Enterprise Transactions: Business Intelligence and Wash and Spoof Transactions in Blockchain and Social Commerce
Real-Time Business Intelligence in Agent-Oriented Supply Chain
Multidimensional Modeling for Social Business Intelligence
Organization Effectiveness and Business Intelligence Systems
Rationalizing Business Intelligence Systems and Explicit Knowledge Objects: Improving Evidence-Based Management in Government Programs
Enterprise Business Intelligence: Data Mining & Machine Learning
Artificial Intelligence Questions
Economic Topics
Data Mining Titles
Accountability Titles
Balanced Scorecard Ideas
Agile Project Management Research Topics
Business Structure Titles
Auditing Paper Topics
Chicago (A-D)
Chicago (N-B)

IvyPanda. (2024, March 2). 75 Business Intelligence Essay Topic Ideas & Examples. https://ivypanda.com/essays/topic/business-intelligence-essay-topics/

"75 Business Intelligence Essay Topic Ideas & Examples." IvyPanda , 2 Mar. 2024, ivypanda.com/essays/topic/business-intelligence-essay-topics/.

IvyPanda . (2024) '75 Business Intelligence Essay Topic Ideas & Examples'. 2 March.

IvyPanda . 2024. "75 Business Intelligence Essay Topic Ideas & Examples." March 2, 2024. https://ivypanda.com/essays/topic/business-intelligence-essay-topics/.

1. IvyPanda . "75 Business Intelligence Essay Topic Ideas & Examples." March 2, 2024. https://ivypanda.com/essays/topic/business-intelligence-essay-topics/.

Bibliography

IvyPanda . "75 Business Intelligence Essay Topic Ideas & Examples." March 2, 2024. https://ivypanda.com/essays/topic/business-intelligence-essay-topics/.

Bibliography
More Referencing guides Blog Automated transliteration Relevant bibliographies by topics
Automated transliteration
Relevant bibliographies by topics
Referencing guides

Dissertations / Theses on the topic 'Business intelligence – Data processing'

Create a spot-on reference in apa, mla, chicago, harvard, and other styles.

Consult the top 50 dissertations / theses for your research on the topic 'Business intelligence – Data processing.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.

Šídlo, Petr. "Návrh projektu business intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2007. http://www.nusl.cz/ntk/nusl-15865.

Marquardt, Justus. "Metadatendesign zur Integration von online analytical processing in das Wissensmanagement." Hamburg Kovač, 2007. http://www.verlagdrkovac.de/978-3-8300-3598-5.htm.

Idris, Muhammad. "Real-time Business Intelligence through Compact and Efficient Query Processing Under Updates." Doctoral thesis, Universite Libre de Bruxelles, 2019. https://dipot.ulb.ac.be/dspace/bitstream/2013/284705/5/contratMI.pdf.

Issa, Carla Mounir. "Data warehouse applications in modern day business." CSUSB ScholarWorks, 2002. https://scholarworks.lib.csusb.edu/etd-project/2148.

Westerlund, Elisabeth, and Hanna Persson. "Implementation of Business Intelligence Systems : A study of possibilities and difficulties in small IT-enterprises." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-255915.

Marquardt, Justus. "Metadatendesign zur Integration von Online Analytical Processing in das Wissensmanagement /." Hamburg : Kovač, 2008. http://www.verlagdrkovac.de/978-3-8300-3598-5.htm.

Ng, Faria Yuen-yi. "Intelligent agents for electronic commerce in tourism." Thesis, University of Surrey, 1999. http://epubs.surrey.ac.uk/844141/.

Lu, Yapeng, and 呂亞鵬. "An integrated algorithm for distributed optimization in networked systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43224234.

Calin, Beatrice Andreea. "Manufacturing Analytics Dashboard: analisi efficienza ed efficacia dei processi produttivi tramite indicatore OEE basata su un MES Data Warehouse." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

Mašek, Martin. "Datové sklady - principy, metody návrhu, nástroje, aplikace, návrh konkrétního řešení." Master's thesis, Vysoká škola ekonomická v Praze, 2007. http://www.nusl.cz/ntk/nusl-10145.

Soukup, Petr. "High-Performance Analytics (HPA)." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-165252.

Cígler, Lukáš. "Možnosti In-memory reportingových nástrojů." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-197493.

Veselý, Jan. "Implementace BI v servisním oddělení telekomunikační společnosti." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-165129.

Munnecom, Lorenna, and Miguel Chaves de Lemos Pacheco. "Exploration of an Automated Motivation Letter Scoring System to Emulate Human Judgement." Thesis, Högskolan Dalarna, Mikrodataanalys, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:du-34563.

Pohl, Ondřej. "Analýza veřejně dostupných dat Českého statistického úřadu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363884.

Slimani, Noureddine. "Integrazione e warehousing dati in ambito BPM." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

Dzimko, Miroslav. "Řešení Business Intelligence." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-318585.

Westerlund, Per. "Business Intelligence: Multidimensional Data Analysis." Thesis, Umeå universitet, Institutionen för datavetenskap, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-138758.

Strejčková, Lucie. "Business Intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124609.

Riaz, Amjad. "Syndicate Data Incorporation into Business Intelligence." Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-5349.

Havránek, Denis. "Business Intelligence v pojišťovnictví." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-74868.

Jämsén, J. (Jarmo). "Kypsyysmalli asiakkaiden valmiudesta käyttää business intelligence -järjestelmää." Master's thesis, University of Oulu, 2014. http://urn.fi/URN:NBN:fi:oulu-201402081074.

Pohořelý, Radovan. "Vizualizace kvality dat v Business Intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-76740.

Karlsson, Rebecka. "Data as Intelligence : A Study of Business Intelligence as Decision Support." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Företagsekonomi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-21276.

Kříž, Jan. "Business Intelligence řešení pro společnost 1188." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2015. http://www.nusl.cz/ntk/nusl-224859.

Drdla, Tomáš. "Návrh řešení Business Intelligence." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-241406.

Eggert, Sandy, and Juliane Meier. "Business Intelligence : Lösungen im Überblick." Universität Potsdam, 2010. http://opus.kobv.de/ubp/volltexte/2010/4449/.

El-Najjar, Lin, and Filip Ilic. "Business intelligence för beslutsstöd inom telekommunikationsbolag : Nyttjandet av Business intelligence för att effektivisera affärsprocesser." Thesis, Södertörns högskola, Medieteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-44602.

Pullokkaran, Laijo John. "Analysis of data virtualization & enterprise data standardization in business intelligence." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/90703.

Černý, Lukáš. "Implementace Business intelligence řešení v podniku." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-72480.

Slaninková, Michaela. "Business Intelligence jako nástroj analýzy dat." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2018. http://www.nusl.cz/ntk/nusl-378340.

Valério, Miguel Gomes Lage. "Dicoogle analytics for business intelligence." Master's thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/17573.

Marjamäki, P. (Pekka). "Evolution and trends of business intelligence systems:a systematic mapping study." Master's thesis, University of Oulu, 2017. http://urn.fi/URN:NBN:fi:oulu-201705031654.

Somasekaram, Premathas. "Designing a Business Intelligence Solution for Analyzing Security Data." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-208685.

Herzberg, Nico, and Mathias Weske. "Enriching raw events to enable process intelligence : research challenges." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6401/.

Filipčík, Zdeněk. "Nástroje Business Intelligence jako Open Source." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-150123.

Musil, Jiří. "Business intelligence v laboratorní firmě." Master's thesis, Vysoká škola ekonomická v Praze, 2016. http://www.nusl.cz/ntk/nusl-204855.

Guan, Zhong Lai. "Trust in Data : Prerequisite for Self-Service Business Intelligence Adoption by Business Users." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104467.

Bravo, Mariangeles, and Jesper Appelkvist. "Towards the Development of Business Intelligence : The Role of Business Intelligence in Managerial Decision Making - Evidence from the B2B Sector." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-76290.

Safari, Arash. "Visualization of E-commerce Transaction Data : USING BUSINESS INTELLIGENCE TOOLS." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177461.

Tashakor, Ghazal. "Delivering Business Intelligence Performance by Data Warehouse and ETL Tuning." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-20062.

Beránková, Kateřina. "Návrh řešení Business Intelligence pro autodopravu." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-197486.

Roman, Martin. "Možnosti využitia Business Intelligence nástrojov v cloude." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-163973.

Choy, Wing Yiu. "Using numerical methods and artificial intelligence in NMR data processing and analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0024/NQ50131.pdf.

Choy, Wing Yiu 1969. "Using numerical methods and artificial intelligence in NMR data processing and analysis." Thesis, McGill University, 1998. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35864.

McHenry, John James. "Exploring Best Practices to Utilize Business Intelligence Systems." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2742.

Devarapalli, Surendra. "AGILE BUSINESS INTELLIGENCE DEVELOPMENT CORE PRACTICES." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-17241.

Škapa, Martin. "Návrh a implementace Business Intelligence systému." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2009. http://www.nusl.cz/ntk/nusl-222228.

Huňáček, Tomáš. "Návrh agilní metodiky pro Business Intelligence projekty." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-206981.

Shahini, Rei. "Business Intelligence in the Hotel Industry." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-100845.

How It Works
PhD thesis writing
Master thesis writing
Bachelor thesis writing
Dissertation writing service
Dissertation abstract writing
Thesis proposal writing
Thesis editing service
Thesis proofreading service
Thesis formatting service
Coursework writing service
Research paper writing service
Architecture thesis writing
Computer science thesis writing
Engineering thesis writing
History thesis writing
MBA thesis writing
Nursing dissertation writing
Psychology dissertation writing
Sociology thesis writing
Statistics dissertation writing
Buy dissertation online
Write my dissertation
Cheap thesis
Cheap dissertation
Custom dissertation
Dissertation help
Pay for thesis
Pay for dissertation
Senior thesis
Write my thesis

214 Best Big Data Research Topics for Your Thesis Paper

Finding an ideal big data research topic can take you a long time. Big data, IoT, and robotics have evolved. The future generations will be immersed in major technologies that will make work easier. Work that was done by 10 people will now be done by one person or a machine. This is amazing because, in as much as there will be job loss, more jobs will be created. It is a win-win for everyone.

Big data is a major topic that is being embraced globally. Data science and analytics are helping institutions, governments, and the private sector. We will share with you the best big data research topics.

On top of that, we can offer you the best writing tips to ensure you prosper well in your academics. As students in the university, you need to do proper research to get top grades. Hence, you can consult us if in need of research paper writing services.

Big Data Analytics Research Topics for your Research Project

Are you looking for an ideal big data analytics research topic? Once you choose a topic, consult your professor to evaluate whether it is a great topic. This will help you to get good grades.

Which are the best tools and software for big data processing?
Evaluate the security issues that face big data.
An analysis of large-scale data for social networks globally.
The influence of big data storage systems.
The best platforms for big data computing.
The relation between business intelligence and big data analytics.
The importance of semantics and visualization of big data.
Analysis of big data technologies for businesses.
The common methods used for machine learning in big data.
The difference between self-turning and symmetrical spectral clustering.
The importance of information-based clustering.
Evaluate the hierarchical clustering and density-based clustering application.
How is data mining used to analyze transaction data?
The major importance of dependency modeling.
The influence of probabilistic classification in data mining.

Interesting Big Data Analytics Topics

Who said big data had to be boring? Here are some interesting big data analytics topics that you can try. They are based on how some phenomena are done to make the world a better place.

Discuss the privacy issues in big data.
Evaluate the storage systems of scalable in big data.
The best big data processing software and tools.
Data mining tools and techniques are popularly used.
Evaluate the scalable architectures for parallel data processing.
The major natural language processing methods.
Which are the best big data tools and deployment platforms?
The best algorithms for data visualization.
Analyze the anomaly detection in cloud servers
The scrutiny normally done for the recruitment of big data job profiles.
The malicious user detection in big data collection.
Learning long-term dependencies via the Fourier recurrent units.
Nomadic computing for big data analytics.
The elementary estimators for graphical models.
The memory-efficient kernel approximation.

Big Data Latest Research Topics

Do you know the latest research topics at the moment? These 15 topics will help you to dive into interesting research. You may even build on research done by other scholars.

Evaluate the data mining process.
The influence of the various dimension reduction methods and techniques.
The best data classification methods.
The simple linear regression modeling methods.
Evaluate the logistic regression modeling.
What are the commonly used theorems?
The influence of cluster analysis methods in big data.
The importance of smoothing methods analysis in big data.
How is fraud detection done through AI?
Analyze the use of GIS and spatial data.
How important is artificial intelligence in the modern world?
What is agile data science?
Analyze the behavioral analytics process.
Semantic analytics distribution.
How is domain knowledge important in data analysis?

Big Data Debate Topics

If you want to prosper in the field of big data, you need to try even hard topics. These big data debate topics are interesting and will help you to get a better understanding.

The difference between big data analytics and traditional data analytics methods.
Why do you think the organization should think beyond the Hadoop hype?
Does the size of the data matter more than how recent the data is?
Is it true that bigger data are not always better?
The debate of privacy and personalization in maintaining ethics in big data.
The relation between data science and privacy.
Do you think data science is a rebranding of statistics?
Who delivers better results between data scientists and domain experts?
According to your view, is data science dead?
Do you think analytics teams need to be centralized or decentralized?
The best methods to resource an analytics team.
The best business case for investing in analytics.
The societal implications of the use of predictive analytics within Education.
Is there a need for greater control to prevent experimentation on social media users without their consent?
How is the government using big data; for the improvement of public statistics or to control the population?

University Dissertation Topics on Big Data

Are you doing your Masters or Ph.D. and wondering the best dissertation topic or thesis to do? Why not try any of these? They are interesting and based on various phenomena. While doing the research ensure you relate the phenomenon with the current modern society.

The machine learning algorithms are used for fall recognition.
The divergence and convergence of the internet of things.
The reliable data movements using bandwidth provision strategies.
How is big data analytics using artificial neural networks in cloud gaming?
How is Twitter accounts classification done using network-based features?
How is online anomaly detection done in the cloud collaborative environment?
Evaluate the public transportation insights provided by big data.
Evaluate the paradigm for cancer patients using the nursing EHR to predict the outcome.
Discuss the current data lossless compression in the smart grid.
How does online advertising traffic prediction helps in boosting businesses?
How is the hyperspectral classification done using the multiple kernel learning paradigm?
The analysis of large data sets downloaded from websites.
How does social media data help advertising companies globally?
Which are the systems recognizing and enforcing ownership of data records?
The alternate possibilities emerging for edge computing.

The Best Big Data Analysis Research Topics and Essays

There are a lot of issues that are associated with big data. Here are some of the research topics that you can use in your essays. These topics are ideal whether in high school or college.

The various errors and uncertainty in making data decisions.
The application of big data on tourism.
The automation innovation with big data or related technology
The business models of big data ecosystems.
Privacy awareness in the era of big data and machine learning.
The data privacy for big automotive data.
How is traffic managed in defined data center networks?
Big data analytics for fault detection.
The need for machine learning with big data.
The innovative big data processing used in health care institutions.
The money normalization and extraction from texts.
How is text categorization done in AI?
The opportunistic development of data-driven interactive applications.
The use of data science and big data towards personalized medicine.
The programming and optimization of big data applications.

The Latest Big Data Research Topics for your Research Proposal

Doing a research proposal can be hard at first unless you choose an ideal topic. If you are just diving into the big data field, you can use any of these topics to get a deeper understanding.

The data-centric network of things.
Big data management using artificial intelligence supply chain.
The big data analytics for maintenance.
The high confidence network predictions for big biological data.
The performance optimization techniques and tools for data-intensive computation platforms.
The predictive modeling in the legal context.
Analysis of large data sets in life sciences.
How to understand the mobility and transport modal disparities sing emerging data sources?
How do you think data analytics can support asset management decisions?
An analysis of travel patterns for cellular network data.
The data-driven strategic planning for citywide building retrofitting.
How is money normalization done in data analytics?
Major techniques used in data mining.
The big data adaptation and analytics of cloud computing.
The predictive data maintenance for fault diagnosis.

Interesting Research Topics on A/B Testing In Big Data

A/B testing topics are different from the normal big data topics. However, you use an almost similar methodology to find the reasons behind the issues. These topics are interesting and will help you to get a deeper understanding.

How is ultra-targeted marketing done?
The transition of A/B testing from digital to offline.
How can big data and A/B testing be done to win an election?
Evaluate the use of A/B testing on big data
Evaluate A/B testing as a randomized control experiment.
How does A/B testing work?
The mistakes to avoid while conducting the A/B testing.
The most ideal time to use A/B testing.
The best way to interpret results for an A/B test.
The major principles of A/B tests.
Evaluate the cluster randomization in big data
The best way to analyze A/B test results and the statistical significance.
How is A/B testing used in boosting businesses?
The importance of data analysis in conversion research
The importance of A/B testing in data science.

Amazing Research Topics on Big Data and Local Governments

Governments are now using big data to make the lives of the citizens better. This is in the government and the various institutions. They are based on real-life experiences and making the world better.

Assess the benefits and barriers of big data in the public sector.
The best approach to smart city data ecosystems.
The big analytics used for policymaking.
Evaluate the smart technology and emergence algorithm bureaucracy.
Evaluate the use of citizen scoring in public services.
An analysis of the government administrative data globally.
The public values are found in the era of big data.
Public engagement on local government data use.
Data analytics use in policymaking.
How are algorithms used in public sector decision-making?
The democratic governance in the big data era.
The best business model innovation to be used in sustainable organizations.
How does the government use the collected data from various sources?
The role of big data for smart cities.
How does big data play a role in policymaking?

Easy Research Topics on Big Data

Who said big data topics had to be hard? Here are some of the easiest research topics. They are based on data management, research, and data retention. Pick one and try it!

Who uses big data analytics?
Evaluate structure machine learning.
Explain the whole deep learning process.
Which are the best ways to manage platforms for enterprise analytics?
Which are the new technologies used in data management?
What is the importance of data retention?
The best way to work with images is when doing research.
The best way to promote research outreach is through data management.
The best way to source and manage external data.
Does machine learning improve the quality of data?
Describe the security technologies that can be used in data protection.
Evaluate token-based authentication and its importance.
How can poor data security lead to the loss of information?
How to determine secure data.
What is the importance of centralized key management?

Unique IoT and Big Data Research Topics

Internet of Things has evolved and many devices are now using it. There are smart devices, smart cities, smart locks, and much more. Things can now be controlled by the touch of a button.

Evaluate the 5G networks and IoT.
Analyze the use of Artificial intelligence in the modern world.
How do ultra-power IoT technologies work?
Evaluate the adaptive systems and models at runtime.
How have smart cities and smart environments improved the living space?
The importance of the IoT-based supply chains.
How does smart agriculture influence water management?
The internet applications naming and identifiers.
How does the smart grid influence energy management?
Which are the best design principles for IoT application development?
The best human-device interactions for the Internet of Things.
The relation between urban dynamics and crowdsourcing services.
The best wireless sensor network for IoT security.
The best intrusion detection in IoT.
The importance of big data on the Internet of Things.

Big Data Database Research Topics You Should Try

Big data is broad and interesting. These big data database research topics will put you in a better place in your research. You also get to evaluate the roles of various phenomena.

The best cloud computing platforms for big data analytics.
The parallel programming techniques for big data processing.
The importance of big data models and algorithms in research.
Evaluate the role of big data analytics for smart healthcare.
How is big data analytics used in business intelligence?
The best machine learning methods for big data.
Evaluate the Hadoop programming in big data analytics.
What is privacy-preserving to big data analytics?
The best tools for massive big data processing
IoT deployment in Governments and Internet service providers.
How will IoT be used for future internet architectures?
How does big data close the gap between research and implementation?
What are the cross-layer attacks in IoT?
The influence of big data and smart city planning in society.
Why do you think user access control is important?

Big Data Scala Research Topics

Scala is a programming language that is used in data management. It is closely related to other data programming languages. Here are some of the best scala questions that you can research.

Which are the most used languages in big data?
How is scala used in big data research?
Is scala better than Java in big data?
How is scala a concise programming language?
How does the scala language stream process in real-time?
Which are the various libraries for data science and data analysis?
How does scala allow imperative programming in data collection?
Evaluate how scala includes a useful REPL for interaction.
Evaluate scala’s IDE support.
The data catalog reference model.
Evaluate the basics of data management and its influence on research.
Discuss the behavioral analytics process.
What can you term as the experience economy?
The difference between agile data science and scala language.
Explain the graph analytics process.

Independent Research Topics for Big Data

These independent research topics for big data are based on the various technologies and how they are related. Big data will greatly be important for modern society.

The biggest investment is in big data analysis.
How are multi-cloud and hybrid settings deep roots?
Why do you think machine learning will be in focus for a long while?
Discuss in-memory computing.
What is the difference between edge computing and in-memory computing?
The relation between the Internet of things and big data.
How will digital transformation make the world a better place?
How does data analysis help in social network optimization?
How will complex big data be essential for future enterprises?
Compare the various big data frameworks.
The best way to gather and monitor traffic information using the CCTV images
Evaluate the hierarchical structure of groups and clusters in the decision tree.
Which are the 3D mapping techniques for live streaming data.
How does machine learning help to improve data analysis?
Evaluate DataStream management in task allocation.
How is big data provisioned through edge computing?
The model-based clustering of texts.
The best ways to manage big data.
The use of machine learning in big data.

Is Your Big Data Thesis Giving You Problems?

These are some of the best topics that you can use to prosper in your studies. Not only are they easy to research but also reflect on real-time issues. Whether in University or college, you need to put enough effort into your studies to prosper. However, if you have time constraints, we can provide professional writing help. Are you looking for online expert writers? Look no further, we will provide quality work at a cheap price.

Research Topics & Ideas: Finance

120+ Finance Research Topic Ideas To Fast-Track Your Project

If you’re just starting out exploring potential research topics for your finance-related dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research topic ideation process by providing a hearty list of finance-centric research topics and ideas.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . To develop a suitable education-related research topic, you’ll need to identify a clear and convincing research gap , and a viable plan of action to fill that gap.

If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, if you’d like hands-on help, consider our 1-on-1 coaching service .

Overview: Finance Research Topics

Corporate finance topics
Investment banking topics
Private equity & VC
Asset management
Hedge funds
Financial planning & advisory
Quantitative finance
Treasury management
Financial technology (FinTech)
Commercial banking
International finance

Corporate Finance

These research topic ideas explore a breadth of issues ranging from the examination of capital structure to the exploration of financial strategies in mergers and acquisitions.

Evaluating the impact of capital structure on firm performance across different industries
Assessing the effectiveness of financial management practices in emerging markets
A comparative analysis of the cost of capital and financial structure in multinational corporations across different regulatory environments
Examining how integrating sustainability and CSR initiatives affect a corporation’s financial performance and brand reputation
Analysing how rigorous financial analysis informs strategic decisions and contributes to corporate growth
Examining the relationship between corporate governance structures and financial performance
A comparative analysis of financing strategies among mergers and acquisitions
Evaluating the importance of financial transparency and its impact on investor relations and trust
Investigating the role of financial flexibility in strategic investment decisions during economic downturns
Investigating how different dividend policies affect shareholder value and the firm’s financial performance

Investment Banking

The list below presents a series of research topics exploring the multifaceted dimensions of investment banking, with a particular focus on its evolution following the 2008 financial crisis.

Analysing the evolution and impact of regulatory frameworks in investment banking post-2008 financial crisis
Investigating the challenges and opportunities associated with cross-border M&As facilitated by investment banks.
Evaluating the role of investment banks in facilitating mergers and acquisitions in emerging markets
Analysing the transformation brought about by digital technologies in the delivery of investment banking services and its effects on efficiency and client satisfaction.
Evaluating the role of investment banks in promoting sustainable finance and the integration of Environmental, Social, and Governance (ESG) criteria in investment decisions.
Assessing the impact of technology on the efficiency and effectiveness of investment banking services
Examining the effectiveness of investment banks in pricing and marketing IPOs, and the subsequent performance of these IPOs in the stock market.
A comparative analysis of different risk management strategies employed by investment banks
Examining the relationship between investment banking fees and corporate performance
A comparative analysis of competitive strategies employed by leading investment banks and their impact on market share and profitability

Private Equity & Venture Capital (VC)

These research topic ideas are centred on venture capital and private equity investments, with a focus on their impact on technological startups, emerging technologies, and broader economic ecosystems.

Investigating the determinants of successful venture capital investments in tech startups
Analysing the trends and outcomes of venture capital funding in emerging technologies such as artificial intelligence, blockchain, or clean energy
Assessing the performance and return on investment of different exit strategies employed by venture capital firms
Assessing the impact of private equity investments on the financial performance of SMEs
Analysing the role of venture capital in fostering innovation and entrepreneurship
Evaluating the exit strategies of private equity firms: A comparative analysis
Exploring the ethical considerations in private equity and venture capital financing
Investigating how private equity ownership influences operational efficiency and overall business performance
Evaluating the effectiveness of corporate governance structures in companies backed by private equity investments
Examining how the regulatory environment in different regions affects the operations, investments and performance of private equity and venture capital firms

Research Topic Kickstarter - Need Help Finding A Research Topic?

Asset Management

This list includes a range of research topic ideas focused on asset management, probing into the effectiveness of various strategies, the integration of technology, and the alignment with ethical principles among other key dimensions.

Analysing the effectiveness of different asset allocation strategies in diverse economic environments
Analysing the methodologies and effectiveness of performance attribution in asset management firms
Assessing the impact of environmental, social, and governance (ESG) criteria on fund performance
Examining the role of robo-advisors in modern asset management
Evaluating how advancements in technology are reshaping portfolio management strategies within asset management firms
Evaluating the performance persistence of mutual funds and hedge funds
Investigating the long-term performance of portfolios managed with ethical or socially responsible investing principles
Investigating the behavioural biases in individual and institutional investment decisions
Examining the asset allocation strategies employed by pension funds and their impact on long-term fund performance
Assessing the operational efficiency of asset management firms and its correlation with fund performance

Hedge Funds

Here we explore research topics related to hedge fund operations and strategies, including their implications on corporate governance, financial market stability, and regulatory compliance among other critical facets.

Assessing the impact of hedge fund activism on corporate governance and financial performance
Analysing the effectiveness and implications of market-neutral strategies employed by hedge funds
Investigating how different fee structures impact the performance and investor attraction to hedge funds
Evaluating the contribution of hedge funds to financial market liquidity and the implications for market stability
Analysing the risk-return profile of hedge fund strategies during financial crises
Evaluating the influence of regulatory changes on hedge fund operations and performance
Examining the level of transparency and disclosure practices in the hedge fund industry and its impact on investor trust and regulatory compliance
Assessing the contribution of hedge funds to systemic risk in financial markets, and the effectiveness of regulatory measures in mitigating such risks
Examining the role of hedge funds in financial market stability
Investigating the determinants of hedge fund success: A comparative analysis

Financial Planning and Advisory

This list explores various research topic ideas related to financial planning, focusing on the effects of financial literacy, the adoption of digital tools, taxation policies, and the role of financial advisors.

Evaluating the impact of financial literacy on individual financial planning effectiveness
Analysing how different taxation policies influence financial planning strategies among individuals and businesses
Evaluating the effectiveness and user adoption of digital tools in modern financial planning practices
Investigating the adequacy of long-term financial planning strategies in ensuring retirement security
Assessing the role of financial education in shaping financial planning behaviour among different demographic groups
Examining the impact of psychological biases on financial planning and decision-making, and strategies to mitigate these biases
Assessing the behavioural factors influencing financial planning decisions
Examining the role of financial advisors in managing retirement savings
A comparative analysis of traditional versus robo-advisory in financial planning
Investigating the ethics of financial advisory practices

Free Webinar: How To Find A Dissertation Research Topic

The following list delves into research topics within the insurance sector, touching on the technological transformations, regulatory shifts, and evolving consumer behaviours among other pivotal aspects.

Analysing the impact of technology adoption on insurance pricing and risk management
Analysing the influence of Insurtech innovations on the competitive dynamics and consumer choices in insurance markets
Investigating the factors affecting consumer behaviour in insurance product selection and the role of digital channels in influencing decisions
Assessing the effect of regulatory changes on insurance product offerings
Examining the determinants of insurance penetration in emerging markets
Evaluating the operational efficiency of claims management processes in insurance companies and its impact on customer satisfaction
Examining the evolution and effectiveness of risk assessment models used in insurance underwriting and their impact on pricing and coverage
Evaluating the role of insurance in financial stability and economic development
Investigating the impact of climate change on insurance models and products
Exploring the challenges and opportunities in underwriting cyber insurance in the face of evolving cyber threats and regulations

Quantitative Finance

These topic ideas span the development of asset pricing models, evaluation of machine learning algorithms, and the exploration of ethical implications among other pivotal areas.

Developing and testing new quantitative models for asset pricing
Analysing the effectiveness and limitations of machine learning algorithms in predicting financial market movements
Assessing the effectiveness of various risk management techniques in quantitative finance
Evaluating the advancements in portfolio optimisation techniques and their impact on risk-adjusted returns
Evaluating the impact of high-frequency trading on market efficiency and stability
Investigating the influence of algorithmic trading strategies on market efficiency and liquidity
Examining the risk parity approach in asset allocation and its effectiveness in different market conditions
Examining the application of machine learning and artificial intelligence in quantitative financial analysis
Investigating the ethical implications of quantitative financial innovations
Assessing the profitability and market impact of statistical arbitrage strategies considering different market microstructures

Treasury Management

The following topic ideas explore treasury management, focusing on modernisation through technological advancements, the impact on firm liquidity, and the intertwined relationship with corporate governance among other crucial areas.

Analysing the impact of treasury management practices on firm liquidity and profitability
Analysing the role of automation in enhancing operational efficiency and strategic decision-making in treasury management
Evaluating the effectiveness of various cash management strategies in multinational corporations
Investigating the potential of blockchain technology in streamlining treasury operations and enhancing transparency
Examining the role of treasury management in mitigating financial risks
Evaluating the accuracy and effectiveness of various cash flow forecasting techniques employed in treasury management
Assessing the impact of technological advancements on treasury management operations
Examining the effectiveness of different foreign exchange risk management strategies employed by treasury managers in multinational corporations
Assessing the impact of regulatory compliance requirements on the operational and strategic aspects of treasury management
Investigating the relationship between treasury management and corporate governance

Financial Technology (FinTech)

The following research topic ideas explore the transformative potential of blockchain, the rise of open banking, and the burgeoning landscape of peer-to-peer lending among other focal areas.

Evaluating the impact of blockchain technology on financial services
Investigating the implications of open banking on consumer data privacy and financial services competition
Assessing the role of FinTech in financial inclusion in emerging markets
Analysing the role of peer-to-peer lending platforms in promoting financial inclusion and their impact on traditional banking systems
Examining the cybersecurity challenges faced by FinTech firms and the regulatory measures to ensure data protection and financial stability
Examining the regulatory challenges and opportunities in the FinTech ecosystem
Assessing the impact of artificial intelligence on the delivery of financial services, customer experience, and operational efficiency within FinTech firms
Analysing the adoption and impact of cryptocurrencies on traditional financial systems
Investigating the determinants of success for FinTech startups

Commercial Banking

These topic ideas span commercial banking, encompassing digital transformation, support for small and medium-sized enterprises (SMEs), and the evolving regulatory and competitive landscape among other key themes.

Assessing the impact of digital transformation on commercial banking services and competitiveness
Analysing the impact of digital transformation on customer experience and operational efficiency in commercial banking
Evaluating the role of commercial banks in supporting small and medium-sized enterprises (SMEs)
Investigating the effectiveness of credit risk management practices and their impact on bank profitability and financial stability
Examining the relationship between commercial banking practices and financial stability
Evaluating the implications of open banking frameworks on the competitive landscape and service innovation in commercial banking
Assessing how regulatory changes affect lending practices and risk appetite of commercial banks
Examining how commercial banks are adapting their strategies in response to competition from FinTech firms and changing consumer preferences
Analysing the impact of regulatory compliance on commercial banking operations
Investigating the determinants of customer satisfaction and loyalty in commercial banking

International Finance

The folowing research topic ideas are centred around international finance and global economic dynamics, delving into aspects like exchange rate fluctuations, international financial regulations, and the role of international financial institutions among other pivotal areas.

Analysing the determinants of exchange rate fluctuations and their impact on international trade
Analysing the influence of global trade agreements on international financial flows and foreign direct investments
Evaluating the effectiveness of international portfolio diversification strategies in mitigating risks and enhancing returns
Evaluating the role of international financial institutions in global financial stability
Investigating the role and implications of offshore financial centres on international financial stability and regulatory harmonisation
Examining the impact of global financial crises on emerging market economies
Examining the challenges and regulatory frameworks associated with cross-border banking operations
Assessing the effectiveness of international financial regulations
Investigating the challenges and opportunities of cross-border mergers and acquisitions

Choosing A Research Topic

These finance-related research topic ideas are starting points to guide your thinking. They are intentionally very broad and open-ended. By engaging with the currently literature in your field of interest, you’ll be able to narrow down your focus to a specific research gap .

When choosing a topic , you’ll need to take into account its originality, relevance, feasibility, and the resources you have at your disposal. Make sure to align your interest and expertise in the subject with your university program’s specific requirements. Always consult your academic advisor to ensure that your chosen topic not only meets the academic criteria but also provides a valuable contribution to the field.

If you need a helping hand, feel free to check out our private coaching service here.

You Might Also Like:

Topic Kickstarter: Research topics in education

thank you for suggest those topic, I want to ask you about the subjects related to the fintech, can i measure it and how?

Please guide me on selecting research titles

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

Print Friendly

Business Information Systems and Architecture (BISA) Lab

Master thesis topics, open data use cases.

Over the recent years, more and more data has become openly available on the internet. However, currently this valuable base of information remains largely unused by companies. In order to fill this gap, we develop the Data App Store, an online platform that supports businesses in the discovery, integration and use of open data.

Conduct a case study on the usage of open data in one of partner companies of the Data App Store project, namely Nestlé, Swisscom, and SBB.

Contact: Andreas Lang or Christine Legner

Requirements and Notation for Information Supply Chains

The concept of an information supply chain consists of all activities and work associated with the transformation of raw data to the delivery of information products to the end consumer and involves the participation of several actors. It functions as an analogy to product supply chain. The goal is to understand how data circulates throughout various corporate systems and functions.

Review existing literature on the topic
Identify requirements for Information Supply Chains
Propose a notation scheme
Otto, B., & Ofner, M. (2010). Towards a Process Reference Model for Information Supply Chain Management. ECIS.
Sun, S., & Yen, J. (2005). Information Supply Chain: A Unified Framework for Information-Sharing. ISI.

Contact: Clément Labadie or Christine Legner

A Data Management Perspective on Information Security Frameworks

Information Security is covered by a variety of general purpose frameworks (relating to governance and auditing, among others). Data management is a subset of these topics that falls under the umbrella of these frameworks, and may be either explicitely or implicitely addressed.

Identify security-related data management design areas (e.g. access rights, privacy compliance)
Select and review information security frameworks
Provide a mapping of data management design areas and information security requirements
National Institute of Standards and Technology (NIST), & United States of America. (2014). Framework for Improving Critical Infrastructure Cybersecurity.
De Haes, S., Van Grembergen, W., & Debreceny, R. S. (2013). COBIT 5 and enterprise governance of information technology: Building blocks and research opportunities. Journal of Information Systems, 27(1), 307-324.

Approaches for Big Data Management

Big Data is a relatively new technological trend – as such, the way it should be used and manage in corporate environments still needs further definition. Big data management is the organization, administration and governance of large volumes of both structured and unstructured data.

Review Big Data-related litterature
Identify design areas and requirements for Big Data Management
Suggest an approach for Big Data Management in corporate environments
Chen, J., Chen, Y., Du, X., Li, C., Lu, J., Zhao, S., & Zhou, X. (2013). Big data challenge: a data management perspective. Frontiers of Computer Science, 7, 157-164.
Cohen, E., Hirama, K., & Rossi, R. (2015). Characterizing Big Data Management.

Analytics as a Service: Self-Service Analytics

Analytical solutions are mainly adopted by large enterprises, however cloud services provide a cost-effective approach to support its adoption by a wider range of organizations. In fact, the global analytics as a service (AaaS) market is expected to grow from $5.9 billion in 2015 to $22.24 billion in 2020 (ResearchandMarkets, 2016) . Besides the reduced costs for implementation, several other factors favor cloud services for business analytics, particularly increased agility owing to the scalability of cloud.

Review of literature on cloud analytics to investigate the different features describing AaaS.
Review case studies on self-service analytics and its adoption in organizations.
Analyze requirements for self-service analytics for well-targeted offerings
Baars, H., Kemper, H.-G., 2010. Business intelligence in the cloud? In PACIS , pp. 145.
Demirkan, H., Delen, D., 2013. Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decis. Support Syst. 55, 412–421.
Ereth, J. and Baars, H. Cloud-Based Business Intelligence and Analytics Applications – Business Value and Feasibility. In PACIS 2015 Proceedings . 2015.
Sun, X., Gao, B., Fan, L., An, W., 2012. A Cost-Effective Approach to Delivering Analytics as a Service, in: 2012 IEEE 19th International Conference on Web Services (ICWS). pp. 512–519.

Contact: Dana Naous or Christine Legner

User Preference Models for Cloud Services

By 2020, “more than $1 trillion in IT spending will be directly or indirectly affected by the shift to cloud” (Gartner, 2016) . Cloud services are mainly delivered in three fundamental service models including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Given the rapid increase of cloud service offerings, users are confronted with multiple options. They find it difficult to evaluate cloud services with the various levels of performance and different economic models.

Review of literature on approaches for cloud service selection (SaaS or IaaS).
Analysis of cloud comparison websites to provide practical insights into the must-have features and appreciated attributes by users for selected types of services.
Gathering criteria that fit users’ needs respectively functional, non-functional, operational and economic requirements.
Develop a model or framework combining general criteria for cloud service selection.
Garg, S.K., Versteeg, S., Buyya, R., 2013. A Framework for Ranking of Cloud Computing Services. Future Gener. Comput. Syst. 29, 1012–1023.
Koehler, P., Anandasivam, A., Dan, M.A., 2010. Cloud Services from a Consumer Perspective, in: AMCIS 2010 Proceedings. Lima, Peru, p. 329.
Ma, D., Kauffman, R.J., 2014. Competition between software-as-a-service vendors. IEEE Trans. Eng. Manag. 61, 717–729.
Qu, L., Wang, Y., Orgun, M.A., Liu, L., Liu, H., Bouguettaya, A., 2015. CCCloud: Context-Aware and Credible Cloud Service Selection Based on Subjective Assessment and Objective Assessment. IEEE Trans. Serv. Comput. 8, 369–383.

How it works

Useful Links

How much will your dissertation cost?

Have an expert academic write your dissertation paper!

Dissertation Services

Get unlimited topic ideas and a dissertation plan for just £45.00

Order topics and plan

Get 1 free topic in your area of study with aim and justification

Yes I want the free topic

Business Management Dissertation Topics

Published by Owen Ingram at January 4th, 2023 , Revised On August 15, 2023

A degree in business administration is intended for those wishing to start their own business or expand an existing one. When you choose business management as your field of study, you are not a typical student because you want to learn about all possible aspects of managing a business.

However, if you are struggling to develop a trending and meaningful business management dissertation topic and need a helping hand. There’s no need to worry! Our unique business management dissertation topic ideas have been developed specifically to ensure you have the best idea to investigate as part of your project.

The process of finding and writing a dissertation is time-consuming. To help you with the topic selection and proposal writing, we have compiled a list of several unique and manageable business management dissertation topics. Without further ado, here we go!

International Development Dissertation Topics
Cooperate Governance Dissertation Topics
Business Intelligence Dissertation Topics
Business Information Technology Dissertation Topics
International Business Dissertation Topics
Business Psychology Dissertation Topics
Business Law Dissertation Topics
Project Management Dissertation Topics
Business Dissertation Topics
HRM Dissertation Topics
Management Dissertation Topics
Operations Management Dissertation Topics

Unique Business Management Dissertation Topics

Coordinating communications and teamwork among remote workers
How business attract their customers
Artificial intelligence investment and its effect on customer satisfaction
Impact of globalization on corporate management
Customer viewpoint on how they use their data when using mobile banking
Investigating the procedure for business model innovation
Evaluation of dynamic capability modelling
An investigation of managerial strategies in the hospitality sector
Important project management abilities required to implement a significant change in an organization’s workplace culture
Voice and silence’s effects on destructive leadership
Influence of store atmosphere on customers’ spontaneous buying habits
Evaluating the effect of forwarding integration on operational efficiency
The contribution of employee training and development to surviving the economic crisis
Comparative comparison of the biggest consumer trends in the United States and the United Kingdom in the automotive industry
A case study demonstrating how cutting-edge businesses like Microsoft and Google acquire a competitive edge through efficient technology management in developing nations
To demonstrate the necessity of economic and social variables for developing a viable chemical engineering industry in the UK.
Assessing the full impact of technological advances on business management techniques in America.
A case study showed how top companies such as Microsoft and Google gain a competitive advantage through effective technology management in developing countries.
Illumination of the challenges facing American companies in terms of sustainability and ethical corporate governance
Assessing the significance and value of eBay’s and Craigslist’s e-commerce industry assumptions, alliances and strategic partnership
demonstrating the need for social and economic variables in the development of a viable chemical engineering industry in the UK.
Study of SONY and Microsoft’s employee retention rates while contrasting their approaches to business management
Psychosocial risks’ effects on workplace risk control
Leadership’s function in a company’s transformative shift
Individual performance factors in SMEs
Business tactics to draw in foreign capital
Enterprise social networking platforms’ effects on knowledge management and organizational learning
How do internal marketing and employee empowerment affect organizational productivity?
Improving the sustainability of American business operations worldwide by developing a closed supply chain.

How Can ResearchProspect Help?

ResearchProspect writers can send several custom topic ideas to your email address. Once you have chosen a topic that suits your needs and interests, you can order for our dissertation outline service which will include a brief introduction to the topic, research questions , literature review , methodology , expected results , and conclusion . The dissertation outline will enable you to review the quality of our work before placing the order for our full dissertation writing service!

Choosing a business management dissertation topic can be extremely stressful for anyone. You can research your topics online and find topics on any subject, for example, nursing dissertation topics or even those related to business, such as marketing dissertation topics.

You must consider several factors when choosing your business management dissertation topics, such as your lecturers’ or supervisor’s specifications and guidelines. Those who break the rules will have their dissertations rejected, so it is important to follow them.

To ensure that your dissertation captures the reader’s attention, choose a dissertation topic that is currently popular. Once you have selected a topic, you can take help from proposal writing services before you start working on the actual thesis paper.

Free Dissertation Topic

Phone Number

Academic Level Select Academic Level Undergraduate Graduate PHD

Academic Subject

Area of Research

Frequently Asked Questions

How to find business management dissertation topics.

To discover business management dissertation topics:

Research recent industry challenges.
Analyze emerging trends.
Examine managerial theories.
Consider global perspectives.
Interview professionals.
Select a topic aligning with your career aspirations.

Business Intelligence Dissertation Topics

Business Intelligence Dissertation Topics is an ultramodern skillful playground to creating a new knowledge to accomplish your ultimate goal. We are established our Business Intelligence Dissertation Topics service for budding of students and research scholars who comes from various graduation including BE, BTech, ME, MTech, MSC, MCA, MPhil, MS and PhD. We help and support scholars to gain much practical sources of advice and knowledge which help them to victoriously accomplish their business intelligence, research, thesis or dissertation. We primary hope is to guide you to successfully chosen your Business Intelligence Dissertation Topics corresponding to your interested domain. If you require our help and support, you can move towards quickly. Success made from Teamwork, Teach, Motivation, Inspiration, Vision, and Mentor.

Business Intelligence Dissertation Topics offer massive collections of state-of-the-art research ideas for scholars to select top-notch topics for accomplish their intellectual research. We are recently working in business intelligence concept for master students and research colleagues to upgrade their knowledge. This is an excellent area which we working for students and research scholars. Till now, we are nearly completed 1000+ business intelligence projects in various business intelligence concept such as workflow management, ontology & business rules, business process automation, rule based business intelligence, business computational intelligence, web intelligence and so on. Here our key insights in Business Intelligence,

…”Business Intelligence (BI) refers to set of data analytics applications and practices for the data collection, transformation, analysis and decision making. The main purpose of BI is to make the decisions while using cloud BI, mobile BI, real-time BI, open source BI, location BI, collaborative BI”.

Upcoming Trends in Business Intelligence:

Self Service Business Intelligence
Advanced/Predictive Analytics
Data Governance
Agile BI development
Integrated platforms PM/BI
Analytical Databases
Mobile Business Intelligence
Data Storytelling
Data warehouse Modernization
Spatial or Location Intelligence
Cloud Business Intelligence
Real-time Analytics
Collaborations

New meta-trends in Business Intelligence:

Artificial Intelligence
Cloud Computing
Consumerization
Digitalization

We provide a wide range of development solutions proven in emerging technologies. Our world class experts are so strong and confident to do projects on Business Intelligence. Other than business intelligence dissertation topics , we focus on the following, see our other assistance in below:

Regular research article writing [in the IEEE, Springer, Elsevier proceedings]
Short paper writing [scenario based writing]
Ideas Write-up [contribute with two pages]
Extended Abstracts [contribute with two pages]
Project Report [in the university proceedings]
Presentations preparation [50-slides PPT for complete research]
Proposals for mini/research projects [in the Journal proceedings]
Conference paper writing [sub-phases of your research]

Recent Research Business Intelligence Dissertation Topics:

Agent Implementation for Secure Grouping Internet of Things with Roll Based Hierarch Access Control
Multiple Big Data Analysis Implementation for Business Intelligence
Knowledge Management for Organizational Knowledge Generation in Higher Education Institution
Materialized View Selection Using Particle Swarm Optimization Based on Exchange Function
Paradigm Using Service Oriented Architecture and Computational Intelligence for Business Intelligence Development
The Role of Alignment on Business Process Performance for Business Intelligence Maturity Impact
Novel Paradigm Using Casual Relationship Mining for Stock Trading Analysis
Cloud Computing Technology Based Early Warring Decision Making System for Unconventional Retail Supply Chain
Content Based Data Masking Strategy in Business Intelligence Platform for Built-in Framework
Research on Knowledge Extraction Using Data Mining for Business Operations
Enterprise Resource Management Model for Data Mining, Business Intelligence and predictive Analysis
Network Methodologies Investigation for Open Research Issues and Massive Internet of Things Data Real Time Analytics
Compare Feature Selection Technique Performance with SVM for Detect Network Anomaly
Free Chain Code Based Online Farsi Handwriting Recognition Using Hidden Markov Model
Random Fischer Linear Discriminant Classifier Projections for Multi Class Classification

Achievements – Hadoop Solutions

YouTube Channel

business intelligence master thesis topics

Customer Review

Other Pages

Quick links.

Hadoop Projects
Big Data Projects
Hadoop Thesis
MapReduce Project Ideas
Big Data Analytics Projects

Support Through

Onsite training

3,000,000+ delegates

15,000+ clients

1,000+ locations

KnowledgePass
Log a ticket

01344203999 Available 24/7

12 Best Artificial Intelligence Topics for Research in 2024

Explore the "12 Best Artificial Intelligence Topics for Research in 2024." Dive into the top AI research areas, including Natural Language Processing, Computer Vision, Reinforcement Learning, Explainable AI (XAI), AI in Healthcare, Autonomous Vehicles, and AI Ethics and Bias. Stay ahead of the curve and make informed choices for your AI research endeavours.

Exclusive 40% OFF

Training Outcomes Within Your Budget!

We ensure quality, budget-alignment, and timely delivery by our expert instructors.

Share this Resource

AI Tools in Performance Marketing Training
Deep Learning Course
Natural Language Processing (NLP) Fundamentals with Python
Machine Learning Course
Duet AI for Workspace Training

Table of Contents

1) Top Artificial Intelligence Topics for Research

a) Natural Language Processing

b) Computer vision

c) Reinforcement Learning

d) Explainable AI (XAI)

e) Generative Adversarial Networks (GANs)

f) Robotics and AI

g) AI in healthcare

h) AI for social good

i) Autonomous vehicles

j) AI ethics and bias

2) Conclusion

Natural Language Processing

Natural Language Processing (NLP) is centred around empowering machines to comprehend, interpret, and even generate human language. Within this domain, three distinctive research avenues beckon:

1) Sentiment analysis: This entails the study of methodologies to decipher and discern emotions encapsulated within textual content. Understanding sentiments is pivotal in applications ranging from brand perception analysis to social media insights.

2) Language generation: Generating coherent and contextually apt text is an ongoing pursuit. Investigating mechanisms that allow machines to produce human-like narratives and responses holds immense potential across sectors.

3) Question answering systems: Constructing systems that can grasp the nuances of natural language questions and provide accurate, coherent responses is a cornerstone of NLP research. This facet has implications for knowledge dissemination, customer support, and more.

Computer Vision

Computer Vision, a discipline that bestows machines with the ability to interpret visual data, is replete with intriguing avenues for research:

1) Object detection and tracking: The development of algorithms capable of identifying and tracking objects within images and videos finds relevance in surveillance, automotive safety, and beyond.

2) Image captioning: Bridging the gap between visual and textual comprehension, this research area focuses on generating descriptive captions for images, catering to visually impaired individuals and enhancing multimedia indexing.

3) Facial recognition: Advancements in facial recognition technology hold implications for security, personalisation, and accessibility, necessitating ongoing research into accuracy and ethical considerations.

Reinforcement Learning

Reinforcement Learning revolves around training agents to make sequential decisions in order to maximise rewards. Within this realm, three prominent Artificial Intelligence Topics emerge:

1) Autonomous agents: Crafting AI agents that exhibit decision-making prowess in dynamic environments paves the way for applications like autonomous robotics and adaptive systems.

2) Deep Q-Networks (DQN): Deep Q-Networks, a class of reinforcement learning algorithms, remain under active research for refining value-based decision-making in complex scenarios.

3) Policy gradient methods: These methods, aiming to optimise policies directly, play a crucial role in fine-tuning decision-making processes across domains like gaming, finance, and robotics.

Introduction To Artificial Intelligence Training

Explainable AI (XAI)

The pursuit of Explainable AI seeks to demystify the decision-making processes of AI systems. This area comprises Artificial Intelligence Topics such as:

1) Model interpretability: Unravelling the inner workings of complex models to elucidate the factors influencing their outputs, thus fostering transparency and accountability.

2) Visualising neural networks: Transforming abstract neural network structures into visual representations aids in comprehending their functionality and behaviour.

3) Rule-based systems: Augmenting AI decision-making with interpretable, rule-based systems holds promise in domains requiring logical explanations for actions taken.

Generative Adversarial Networks (GANs)

The captivating world of Generative Adversarial Networks (GANs) unfolds through the interplay of generator and discriminator networks, birthing remarkable research avenues:

1) Image generation: Crafting realistic images from random noise showcases the creative potential of GANs, with applications spanning art, design, and data augmentation.

2) Style transfer: Enabling the transfer of artistic styles between images, merging creativity and technology to yield visually captivating results.

3) Anomaly detection: GANs find utility in identifying anomalies within datasets, bolstering fraud detection, quality control, and anomaly-sensitive industries.

Robotics and AI

The synergy between Robotics and AI is a fertile ground for exploration, with Artificial Intelligence Topics such as:

1) Human-robot collaboration: Research in this arena strives to establish harmonious collaboration between humans and robots, augmenting industry productivity and efficiency.

2) Robot learning: By enabling robots to learn and adapt from their experiences, Researchers foster robots' autonomy and the ability to handle diverse tasks.

3) Ethical considerations: Delving into the ethical implications surrounding AI-powered robots helps establish responsible guidelines for their deployment.

AI in healthcare

AI presents a transformative potential within healthcare, spurring research into:

1) Medical diagnosis: AI aids in accurately diagnosing medical conditions, revolutionising early detection and patient care.

2) Drug discovery: Leveraging AI for drug discovery expedites the identification of potential candidates, accelerating the development of new treatments.

3) Personalised treatment: Tailoring medical interventions to individual patient profiles enhances treatment outcomes and patient well-being.

AI for social good

Harnessing the prowess of AI for Social Good entails addressing pressing global challenges:

1) Environmental monitoring: AI-powered solutions facilitate real-time monitoring of ecological changes, supporting conservation and sustainable practices.

2) Disaster response: Research in this area bolsters disaster response efforts by employing AI to analyse data and optimise resource allocation.

3) Poverty alleviation: Researchers contribute to humanitarian efforts and socioeconomic equality by devising AI solutions to tackle poverty.

Unlock the potential of Artificial Intelligence for effective Project Management with our Artificial Intelligence (AI) for Project Managers Course . Sign up now!

Autonomous vehicles

Autonomous Vehicles represent a realm brimming with potential and complexities, necessitating research in Artificial Intelligence Topics such as:

1) Sensor fusion: Integrating data from diverse sensors enhances perception accuracy, which is essential for safe autonomous navigation.

2) Path planning: Developing advanced algorithms for path planning ensures optimal routes while adhering to safety protocols.

3) Safety and ethics: Ethical considerations, such as programming vehicles to make difficult decisions in potential accident scenarios, require meticulous research and deliberation.

AI ethics and bias

Ethical underpinnings in AI drive research efforts in these directions:

1) Fairness in AI: Ensuring AI systems remain impartial and unbiased across diverse demographic groups.

2) Bias detection and mitigation: Identifying and rectifying biases present within AI models guarantees equitable outcomes.

3) Ethical decision-making: Developing frameworks that imbue AI with ethical decision-making capabilities aligns technology with societal values.

Future of AI

The vanguard of AI beckons Researchers to explore these horizons:

1) Artificial General Intelligence (AGI): Speculating on the potential emergence of AI systems capable of emulating human-like intelligence opens dialogues on the implications and challenges.

2) AI and creativity: Probing the interface between AI and creative domains, such as art and music, unveils the coalescence of human ingenuity and technological prowess.

3) Ethical and regulatory challenges: Researching the ethical dilemmas and regulatory frameworks underpinning AI's evolution fortifies responsible innovation.

AI and education

The intersection of AI and Education opens doors to innovative learning paradigms:

1) Personalised learning: Developing AI systems that adapt educational content to individual learning styles and paces.

2) Intelligent tutoring systems: Creating AI-driven tutoring systems that provide targeted support to students.

3) Educational data mining: Applying AI to analyse educational data for insights into learning patterns and trends.

Unleash the full potential of AI with our comprehensive Introduction to Artificial Intelligence Training . Join now!

Conclusion

The domain of AI is ever-expanding, rich with intriguing topics about Artificial Intelligence that beckon Researchers to explore, question, and innovate. Through the pursuit of these twelve diverse Artificial Intelligence Topics, we pave the way for not only technological advancement but also a deeper understanding of the societal impact of AI. By delving into these realms, Researchers stand poised to shape the trajectory of AI, ensuring it remains a force for progress, empowerment, and positive transformation in our world.

Unlock your full potential with our extensive Personal Development Training Courses. Join today!

Frequently Asked Questions

Upcoming data, analytics & ai resources batches & dates.

Fri 2nd Aug 2024

Fri 15th Nov 2024

Get A Quote

WHO WILL BE FUNDING THE COURSE?

My employer

By submitting your details you agree to be contacted in order to respond to your enquiry

Business Analysis
Lean Six Sigma Certification

Share this course

Our biggest spring sale.

We cannot process your enquiry without contacting you, please tick to confirm your consent to us for contacting you about your enquiry.

By submitting your details you agree to be contacted in order to respond to your enquiry.

We may not have the course you’re looking for. If you enquire or give us a call on 01344203999 and speak to our training experts, we may still be able to help with your training requirements.

Or select from our popular topics

ITIL® Certification
Scrum Certification
Change Management Certification
Business Analysis Courses
Microsoft Azure Certification
Microsoft Excel Courses
Microsoft Project
Explore more courses

Press esc to close

Fill out your contact details below and our training experts will be in touch.

Fill out your contact details below

Thank you for your enquiry!

One of our training experts will be in touch shortly to go over your training requirements.

Back to Course Information

Fill out your contact details below so we can get in touch with you regarding your training requirements.

* WHO WILL BE FUNDING THE COURSE?

Preferred Contact Method

No preference

Back to course information

Fill out your training details below

Fill out your training details below so we have a better idea of what your training requirements are.

HOW MANY DELEGATES NEED TRAINING?

HOW DO YOU WANT THE COURSE DELIVERED?

Online Instructor-led

Online Self-paced

WHEN WOULD YOU LIKE TO TAKE THIS COURSE?

Next 2 - 4 months

WHAT IS YOUR REASON FOR ENQUIRING?

Looking for some information

Looking for a discount

I want to book but have questions

One of our training experts will be in touch shortly to go overy your training requirements.

Your privacy & cookies!

Like many websites we use cookies. We care about your data and experience, so to give you the best possible experience using our site, we store a very limited amount of your data. Continuing to use this site or clicking “Accept & close” means that you agree to our use of cookies. Learn more about our privacy policy and cookie policy cookie policy .

We use cookies that are essential for our site to work. Please visit our cookie policy for more information. To accept all cookies click 'Accept & close'.

Customer Reviews

Please fill the form correctly

Need an essay writer for me? Connect now!

Feeling tired to write drafts on your own or you do not have ample ideas to write with? Be it anything, our writers are here to assist you with the best essay writing service. With our service, you will save a lot of time and get recognition for the academic assignments you are given to write. This will give you ample time to relax as well. Let our experts write for you. With their years of experience in this domain and the knowledge from higher levels of education, the experts can do brilliant essay writing even with strict deadlines. They will get you remarkable remarks on the standard of the academic draft that you will write with us.

Andre Cardoso

Margurite J. Perez

Member Login

Who is an essay writer? 3 types of essay writers

How our paper writing service is used.

We stand for academic honesty and obey all institutional laws. Therefore EssayService strongly advises its clients to use the provided work as a study aid, as a source of ideas and information, or for citations. Work provided by us is NOT supposed to be submitted OR forwarded as a final work. It is meant to be used for research purposes, drafts, or as extra study materials.

IMAGES

MBA Dissertation Topics in Business Intelligence
Powerful MBA Thesis Topics in Human Resources Management Online by
PPT
Master Of Business Intelligence & Data Analytics
(PDF) Business Intelligence
32 Business Intelligence Dissertation Topics Examples

VIDEO

Master Informatique
How to Build Career in Data Analyst in 2024
Top 10 Human Resource Thesis research topics research paper
Actual Thesis Topic
เครื่องมือที่ต้องรู้เมื่อทำวิจัย EP.01: ให้ AI ช่วยหาหัวข้อวิจัย
The Future of Business Intelligence: Beyond 2023

COMMENTS

Top Business Intelligence Research Topics to Choose from in 2024
In 2024, Business Intelligence ( BI) is a rapidly evolving field focusing on data collection, analysis, and interpretation to enhance decision-making in organizations. To contribute meaningfully and stay at the forefront of industry advancements, selecting a compelling research topic is vital. This article explores prominent research subjects ...
Business Intelligence Dissertation Topics
Here are a few interesting and appealing topics for a dissertation on business intelligence. Implementation of a secure grouping agent with model-based organizational control. Business Intelligence Several Big Data analytics and their implementations. Knowledge management facilitates organizational learning in higher education.
20 Great Ideas For An MBA Thesis On Business Intelligence
Top MBA Dissertation Prompts on Business Intelligence. Creating a healthy business environment: data sharing issues. Time for changes: business intelligence innovations in the 21st century. Online data storage for enterprises: the effectiveness and ways for improvement. Meeting the company's information requirements: useful strategies and ...
MBA Research Topics In Business (+ Free Webinar)
Here, we'll explore a variety of research ideas and topic thought-starters for management-related research degrees (MBAs/DBAs, etc.). These research topics span management strategy, HR, finance, operations, international business and leadership. NB - This is just the start…. The topic ideation and evaluation process has multiple steps.
75 Business Intelligence Essay Topic Ideas & Examples
Google Analytics as a Business Intelligence Tool. Google Analytics is considered a powerful freemium tool for Web site and mobile app analysis, making it one of the most successful BI tools with superior return on investment. We will write. a custom essay specifically for you by our professional experts.
PDF MASTER THESIS BY MIKE PADBERG Big Data and Business Intelligence: a
MASTER THESIS Big Data and Business Intelligence: a data-driven strategy for e-commerce organizations in the hotel industry Date 03-09-2015 Personal information Author Mike Padberg E-mail [email protected] Study program Master in Business Administration Business Information Management University of Twente The Netherlands
PDF Evaluating Success and Maturity of Business Intelligence Implementation
This master's thesis would not be possible without my supervisor who has provided his invaluable advices and support. Thank you also for my colleagues who offered ... Business intelligence (BI) systems have been designed to fill this need. BI systems help companies in decision-making by gathering, storing, accessing and
PDF Business Intelligence (BI) strategy development: a grounded ...
Title of thesis . Business Intelligence (BI) strategy development: a grounded action research . Degree . Master of Science in Economics and Business Administration. Degree programme . Information and Service Management . Thesis advisor . Hannu Kivijärvi . Year of approval . 2014 . Number of pages . 134 . Language . English . Abstract ...
Dissertations / Theses on the topic 'Business intelligence
Consult the top 50 dissertations / theses for your research on the topic 'Business intelligence - Data processing.'. Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA ...
PDF Master Thesis Self-Service Business Intelligence success factors that
Master Thesis Self-Service Business Intelligence success factors that create value for ... Subject: Information Systems Level: Graduate Department of Informatics. 2 (53) Abstract Business Intelligence and Analytics have changed the business needs, but the market requires a ... 1.3 Topic justification Business Intelligence tools are a necessity ...
Research Topics & Ideas: Data Science
Data Science-Related Research Topics. Developing machine learning models for real-time fraud detection in online transactions. The use of big data analytics in predicting and managing urban traffic flow. Investigating the effectiveness of data mining techniques in identifying early signs of mental health issues from social media usage.
Business IT Dissertation Topics & Titles
Below Are Some Business Information Technology Dissertation Topics: A literature analysis on the information quality management framework. A comprehensive investigation of the information system hierarchy. Big data and business intelligence are essential for sustainable development in organizations: Discuss a UK-based perspective.
PDF BUSINESS INTELLIGENCE IN STRATEGIC MANAGEMENT
The results of this thesis provided how business intelligence can help in the decision-making process in businesses and how implementing business intelligence will enhance the performance of the organi-zation. Moreover, the results discussed the utilization of business intelligence in strategic management and what benefits a company can get.
214 Big Data Research Topics: Interesting Ideas To Try
These 15 topics will help you to dive into interesting research. You may even build on research done by other scholars. Evaluate the data mining process. The influence of the various dimension reduction methods and techniques. The best data classification methods. The simple linear regression modeling methods.
Help with Thesis topic in Business Intelligence and Analytics
There are many trending available topics. Such as, Data Security. Data Discovery/Visualization. SaaS BI. Predictive And Prescriptive Analytics. Collaborative Business Intelligence. After topic ...
120+ Research Topics In Finance (+ Free Webinar)
If you're just starting out exploring potential research topics for your finance-related dissertation, thesis or research project, you've come to the right place. In this post, we'll help kickstart your research topic ideation process by providing a hearty list of finance-centric research topics and ideas. PS - This is just the start…
Masterthesis
Taking into account your scientific interests, I propose the following topic for your thesis: Improving computerized analytical techniques based on Business Intelligence solutions and the use of ...
Master Thesis Topics
Data management is a subset of these topics that falls under the umbrella of these frameworks, and may be either explicitely or implicitely addressed. Objectives: Identify security-related data management design areas (e.g. access rights, privacy compliance) Select and review information security frameworks. Provide a mapping of data management ...
30 Business Management Dissertation Topics
How business attract their customers. Artificial intelligence investment and its effect on customer satisfaction. Impact of globalization on corporate management. Customer viewpoint on how they use their data when using mobile banking. Investigating the procedure for business model innovation.
Recommendations on Master's Thesis topic about BI?
Business Intelligence is the process of utilizing organizational data, technology, analytics, and the knowledge of subject matter experts to create data-driven decisions via dashboards, reports, alerts, and ad-hoc analysis. ... Master thesis topic in Active inference upvotes ...
Business Intelligence Dissertation Topics
Business Intelligence Dissertation Topics is an ultramodern skillful playground to creating a new knowledge to accomplish your ultimate goal. We are established our Business Intelligence Dissertation Topics service for budding of students and research scholars who comes from various graduation including BE, BTech, ME, MTech, MSC, MCA, MPhil, MS ...
12 Best Artificial Intelligence Topics for Thesis and Research
1) Top Artificial Intelligence Topics for Research. a) Natural Language Processing. b) Computer vision. c) Reinforcement Learning. d) Explainable AI (XAI) e) Generative Adversarial Networks (GANs) f) Robotics and AI. g) AI in healthcare. h) AI for social good.
Business Intelligence Master Thesis Topics
Business Intelligence Master Thesis Topics. Earl M. Kinkade. #10 in Global Rating. 4.9 (2939 reviews) Looking for something more advanced and urgent? Then opt-in for an advanced essay writer who'll bring in more depth to your research and be able to fulfill the task within a limited period of time. In college, there are always assignments ...

Top Business Intelligence Research Topics to Choose from in 2024

Top Business Intelligence Research Topics

How to Write a Perfect Research Paper?

Why Business Intelligence is Important in 2024?

Frequently Asked Questions (FAQs)

Gauri Guglani

Upcoming BI & Visualization Batches & Dates

prive academy

MBA Dissertation Topics On Business Intelligence: 20 Best Ideas

Hints for Finding a Good Dissertation Topic for MBA Level

Top MBA Dissertation Prompts on Business Intelligence

75 Business Intelligence Essay Topic Ideas & Examples

Dissertations / Theses on the topic 'Business intelligence – Data processing'

214 Best Big Data Research Topics for Your Thesis Paper

Big Data Analytics Research Topics for your Research Project

Interesting Big Data Analytics Topics

Big Data Latest Research Topics

Big Data Debate Topics

University Dissertation Topics on Big Data

The Best Big Data Analysis Research Topics and Essays

The Latest Big Data Research Topics for your Research Proposal

Interesting Research Topics on A/B Testing In Big Data

Amazing Research Topics on Big Data and Local Governments

Easy Research Topics on Big Data

Unique IoT and Big Data Research Topics

Big Data Database Research Topics You Should Try

Big Data Scala Research Topics

Independent Research Topics for Big Data

Is Your Big Data Thesis Giving You Problems?

Leave a Reply Cancel reply

Research Topics & Ideas: Finance

Overview: Finance Research Topics

Corporate Finance

Investment Banking

Private Equity & Venture Capital (VC)

Asset Management

Hedge Funds

Financial Planning and Advisory

Quantitative Finance

Treasury Management

Financial Technology (FinTech)

Commercial Banking

International Finance

Choosing A Research Topic

You Might Also Like:

Submit a Comment Cancel reply

Business Information Systems and Architecture (BISA) Lab

Requirements and Notation for Information Supply Chains

A Data Management Perspective on Information Security Frameworks

Approaches for Big Data Management

Analytics as a Service: Self-Service Analytics

User Preference Models for Cloud Services

Useful Links

Business Management Dissertation Topics

Unique Business Management Dissertation Topics

How Can ResearchProspect Help?

Free Dissertation Topic

Frequently Asked Questions

You May Also Like

Business Intelligence Dissertation Topics

Recent Posts

Achievements – Hadoop Solutions

YouTube Channel

Customer Review

Other Pages

Support Through

12 Best Artificial Intelligence Topics for Research in 2024

Training Outcomes Within Your Budget!

Share this Resource

Top Artificial Intelligence Topics for Research

Natural Language Processing

Computer Vision

Reinforcement Learning

Explainable AI (XAI)

Generative Adversarial Networks (GANs)

Robotics and AI

AI in healthcare

AI for social good

Autonomous vehicles

AI ethics and bias