An extreme arm of analytics is “predictive analytics” It’s core lies in data mining - which is nothing but a process used to extract usable data from a larger set of any raw data.

This technique is heavily used in thousands of tools available today in digital marketing landscape. You have experienced automatic predictions yourself in Flipkart - the way more similar products are shown to you marked as “based on your history”

Or, when you happen to buy from Amazon, the flash advertisement they keep showing you for months to come. These businesses are mining your activity data, and using the same to predict behavior. Every major business also has an internal follow up structure. Once your details are in their system, your data may be processed based on various conditions, and possibly even looked at with a qualification score before they call you for more offers or seek feedback. That’s where they are deciding on whether to call you based on your activity on application.

Identifying patterns based on trends, predicting outcomes, being informed with data readily to take business decisions, all are key features of data mining.

Data mining is just one step in the knowledge discovery process. The process also requires identifying the problem to be solved, collecting and preparing the right data, interpreting and deploying models, and monitoring the results.

What it isn’t?

Data mining is just a tool, which needs to be worked with standard requirements. It won’t just sit in your database watching what happens and send you notification to get your attention when it sees an interesting pattern. You still need to know your business, to understand your data, or to understand analytical methods. It does not tell you the value of the patterns to the organization. Pretty much similar to what Machine learning isn’t - this is more about applying human creativity, in addition to working with Data Mining.

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