Welcome to the world of analytics!
In this chapter, we will learn and recap important analytic techniques or methods that data scientists employ and practice as a part of a data science project implementation. For each of the analytic techniques, we will set the context for its application and detail the expected outcome. Additionally, we will learn how to apply R, Weka, MADlib, and Hadoop frameworks and tools for analytics in general as well as in the context of Greenplum.
The following topics are covered in this chapter:
Introduction to standard analytic paradigms: descriptive, predictive, and prescriptive analytics
Dive deep into important analytical methods: simulations, clustering, data mining, text analytics, decision trees, association rules, linear and logistic regression, and so on
Technology and tools:
In-database analytics using MADlib