Chapter 1. Big Data, Analytics, and Data Science Life Cycle

Enterprise data has never been of such prominence as in the recent past. One of the dominant challenges of today's major data influx in enterprises is establishing a future-proof strategy focused on deriving meaningful insights tangibly contributing to business growth.

This chapter introduces readers to the core aspects of Big Data, standard analytical techniques, and data science as a practice in business context. In the chapters that follow, these topics are further elaborated with a step-by-step implementation guide to use Greenplum's Unified Analytics Platform (UAP).

The topics covered in this chapter are listed as follows:

  • Enterprise data and its characteristics
  • Context of Big Data—a definition and the paradigm shift
  • Data formats such as structured, semi-structured, and unstructured data
  • Data analysis, need, and overview of important analytical techniques (statistical, predictive, mining, and so on)
  • The philosophy of data science and its standard life cycle
上一章目录下一章