10 Data Analytics / Mining / and Business Analytics related topics

Ten topics for preparing a predictive Analytics white paper (most popular data analytics research topics for your final year seminar).

If you want more details on data mining, please refer to this: Data Mining Seminar Report.

You can also find several Artificial Intelligence related articles here: AI Seminar Topics

#1. Educational data mining
#2. Business intelligence predictive Analytics
#3. Big data and Business Intelligence(BI) or Market Intelligence (Related: Big Data)
#4. Open-source Data Mining and Open Data visualisation
#5. Data Mining System – Data mining systems process large data sets to identify patterns and trends. They are used in various applications, including marketing, fraud detection, and social media analysis.


#6. Data Mining Trends – Data mining is discovering patterns in large data sets from information technology tools. Data mining tools are widely used by business people to make decisions that can be used for analyzing large quantities of data.
#7. Health data mining
#8. Web Analytics / Search Engine Analytics solution
#9. Data Mining marketing
#10. Data Mining in Search Engine Analytics (related: SEO)

#11. ChatGPT (The most trending technology topic of the year)

#12 Data Mining System

#13 Snowflake

#14 Python Libraries for Data Science

#15 Data Analytics

Related: Data Science Seminar Topics

What are the trending topics related to Predictive Analytics and data mining?

Here is the list of currently trending predictive analytics-related topics [ as of 2024 ]:

  • Chat GPT and Accounting
  • Open AI Chat GPT
  • AI Data Analytics
  • Machine learning in software
  • Prescriptive analytics – Prescriptive analytics is about making predictions and recommendations based on data. By analyzing past data and trends, businesses can make more informed decisions about the future. This analytics type can help enterprises optimize their operations, use resources, and improve customer satisfaction.
  • Google Computer vision
  • Python programming language usage in Data Mining
  • Visualization – Data visualization
  • Regression analysis – It’s a statistical technique that’s used to model relationships between variables.
  • Data set
  • Structure of Data
  • Management of Data
  • Decision-making using Data
  • Computers and information technology
  • Data and information visualization
  • Data governance
  • Data Scraping
  • Organization of Data
  • Unstructured data
  • Automated Machine Learning, or AutoML – Automated machine learning is the process of automating the tasks of applying machine learning to real-world problems.
  • Applications of Artificial Intelligence
  • Statistical classification – As we all know, classification separates items into groups based on specific characteristics. In statistics, classification is assigning data to classes based on statistical properties. There are many different ways to classify, each with advantages and disadvantages.


Are you new to Data Mining? Refer to the Data Mining technical whitepaper. I shall write more articles about these topics in the coming days to help prepare your white papers.

The significance of Data Mining related technologies today.

The following image illustrates why Hadoop/Big Data is essential to you today.

Related Topics

Here are some real-time use of Data Mining

  • Develop a data mining algorithm to identify patterns and trends in large datasets.
  • Use data mining techniques to identify customer behaviour and preferences, which can then be used to tailor marketing strategies.
  • Analyze social media data to identify trends and patterns in user behaviour.
  • Use data mining to identify anomalies or outliers in large datasets, which can be investigated further.
  • Use data mining to predict future trends or events based on historical data.
  • Develop a recommendation engine using data mining techniques to suggest products or content to users based on their past behaviour and preferences.
  • Use data mining to identify potential fraud or security breaches in financial transactions.
  • Analyze healthcare data to identify patterns and trends in patient outcomes and treatment effectiveness.
  • Use data mining to optimize supply chain management by identifying trends in demand and supply.
  • Develop a predictive maintenance system using data mining to identify potential equipment failures before they occur.

Collegelib.com prepared and published this curated list of technologies for Engineering topic preparation. Before shortlisting your topic, you should do your research in addition to this information. Please include Reference: Collegelib.com and link back to Collegelib in your work.

This article was originally published on Collegelib in 2012 and is regularly updated.