- Is There a Difference Between Analytics and Analysis?
- Where Does Data Mining Fit In?
- Why the Sudden Popularity of Analytics?
- The Application Areas of Analytics
- The Main Challenges of Analytics
- A Longitudinal View of Analytics
- A Simple Taxonomy for Analytics
- The Cutting Edge of Analytics: IBM Watson
Where Does Data Mining Fit In?
Data mining is the process of discovering new knowledge in the forms of patterns and relationships in large data sets. The goal of analytics is to convert data/facts into actionable insight, and data mining is the key enabler of that goal. Data mining has been around much longer than analytics, at least in the context of analytics today. As analytics became an overarching term for all decision support and problem-solving techniques and technologies, data mining found itself a rather large space within that arc, ranging from descriptive exploration of identifying relationships and affinities among variables (e.g., market-basket analysis) to developing models to estimate future values of interesting variables. As we will see later in this chapter, within the taxonomy of analytics, data mining plays a key role at every level, from the most simple to the most sophisticated.