A little insight into analytics

Qbase provides a wide range of analytical services. In today's post, we'll take a look at one of the standards of analytics: predictive analytics. Predictive analytics fall into two main categories: statistical and data mining. Now, statistical approaches emerged from statistical theory, as opposed to data mining, which emerged from computational theory. Both statistical analytics and data mining are rooted in mathematics and share many of the same techniques. However, statistical approaches work to uncover the relationships and correlations among the variables in the predictive models, while data mining (also known as “machine learning”) focuses on the predictive capability of the model without regard to explanation. Data mining techniques do not require the user to know the relationships or patterns in the data, nor do they necessarily lead to simple explanations of the relationships. Today’s data mining tools and applications incorporate many of the statistical algorithms traditionally associated with a statistical approach. The tools leave the decision, appropriately, to the analyst.