Future Trends in Data Mining

A futurist is a person who uses a combination of statistics, research, intuition, and imagination to make educated predictions and projections concerning the future. Their predictions can be anything from technological and health trends, to trends in education, evolving demographic patterns, or trends relating to the environment. The first futurists included Sir Isaac Newton’s Mathematical Principle in 1967, then grew into science fiction works authored by H.G. Wells, Isaac Asimov, Arthur C. Clarke, Frank Herbert, among many others. Futurism became a bone fide occupation in the 21st century, with many employers employing futurists without even knowing it. A degree in futurism is not a prerequisite to being a futurist; however Universities such as the University of Hawaii have entire futurism departments such as the Department of Political Science: Future Studies (Parsons, n.d.).

Data mining (DM) is a process under the larger data science umbrella and is also referred to as knowledge management (KM). Today’s data sets used in DM require special software tools for identifying meaning and they also need proper context to help create value in the ocean of data available to us (Yen, 2021). Futurists are hard at work in the data mining field to help bring advancements in:

·        Data dominance in the health care and pharmaceutical fields – The recent rapid advancement of the coronavirus vaccines is attributed to data mining – or more specifically – advancement in signal detection during clinical trial processes for new drugs. These advances are being used to analyze DNA sequences for creating custom therapies, make more informed decisions, and more.

·        Increasing automation in data mining – Artificial intelligence (AI) and machine learning (ML) are replacing previously manual intensive processes for the application of pattern discovery algorithms. Tomorrows data mining will further integrate ML and data stores to provide advanced data management functionality along with new data analysis techniques.

·        The rise of spatial and geographic data mining – With the rapid advancements in space, there has been a new focus on data mining for a multitude of space related use cases from spacecraft design and testing, to zero gravity cancer research, and asteroid mining. Through geographic information systems (GIS), such as GPS powered navigation, and Google Maps, spatial and geographic data mining are quickly becoming fixtures of life.

Business intelligence (BI) concepts refer to the use of digital computing technologies in the forms of analytics, data warehouses, and visualization with the purpose of analyzing and identifying essential business related data to generate new and actionable corporate insights. In simpler terms, BI is the process of discovering valuable trends in data to make more accurate, efficient business decisions related to business strategies, aims, and goals (Data Pine, 2022). We will soon see future trends in BI that specialize in better AI analytics of data mining to find quicker, more useful trends, and requiring less human intervention. I also believe we will start to see, not only the automated, intelligent analysis of this data, but also the automated application of some of these newly discovered trends and patterns.

 

References

A beginner's introduction to Business Intelligence Concepts & BI Basics. Data Pine. (2022, August 30). Retrieved October 4, 2022, from https://www.datapine.com/blog/business-intelligence-concepts-and-bi-basics/#:~:text=Business%20intelligence%20concepts%20refer%20to,generate%20new%2C%20actionable%20corporate%20insights.

Parsons, B. (n.d.). What is a futurist? . benparsons.org. Retrieved October 4, 2022, from https://www.benparsons.org/what-is-a-futurist-an-explanation-of-the-coolest-and-most-important-role-in-society.html

Yen, L. (2021, December 22). Current trends & future scope of Data Mining. Datamation. Retrieved October 4, 2022, from https://www.datamation.com/big-data/data-mining-trends/