Q:  

What is the difference between analytics and data mining? A search on "Ask the Experts" helped me to get the difference between data warehousing and business intelligence but I was not able to find the difference between the analytics and data mining. Please throw some light on this.

A:  

Larissa Moss' Answer: Business analytics is a term that refers to the various modes of using information to make business decisions. Traditionally we used to call this decision support, and it was mostly accomplished through static green-bar paper reports and some ad hoc querying. But in the last decade, the decision-support tools (data warehouse and business intelligence tools) have become more and more sophisticated for data access, data analysis, data manipulation, data mining, forecasting, trend analysis and other metric-based presentations such as scorecards and dashboards. Nowadays, they even include packaged analytical applications for specific business domains, such as supply chain analysis, sales channel analysis, performance analysis, etc. Data mining is a method of pattern discovery against a pool of data using specialized data mining tools. These tools use a sophisticated blend of classical and advanced components like artificial intelligence, pattern recognition, databases, traditional statistics, and graphics to present hidden relationships and patterns they find in any given data pool. One of the official definitions for data mining is: "Data analysis without preconceived hypothesis to unearth unsuspected or unknown relationships, patterns or associations of data." Simply put, "without preconceived hypothesis" means you don't know what exactly you are looking for, "to unearth" means the tool will analyze the data using special algorithms and analytical models to discover any patterns in the data and then tell you about them. The term data mining is sometimes misused to mean "ability to write a lot of different SQL queries."

Sid Adelman's Answer: Both analytics and data mining are aimed at information that is actionable; however, analytics and data mining are as different as chalk and cheese. Analytics usually comes with hypotheses testing. The analyst has something in mind and is looking to answer a question and has a hypotheses about that question. Data mining is more the act of discovery that lacks a hypotheses. Data mining looks, in some cases, for patterns, often through vast amounts of data, and data mining is looking for patterns and relationships that were not anticipated.

Chuck Kelley's Answer: Data mining is exploring data for trends that cannot be "defined" where analytics is looking at data for trends that can be defined.