Chapter 1.  The Big Data Science Ecosystem

As a data scientist, you'll no doubt be very familiar with handling files and processing perhaps even large amounts of data. However, as I'm sure you will agree, doing anything more than a simple analysis over a single type of data requires a method of organizing and cataloguing data so that it can be managed effectively. Indeed, this is the cornerstone of a great data scientist. As the data volume and complexity increases, a consistent and robust approach can be the difference between generalized success and over-fitted failure!

This chapter is an introduction to an approach and ecosystem for achieving success with data at scale. It focuses on the data science tools and technologies. It introduces the environment, and how to configure it appropriately, but also explains some of the nonfunctional considerations relevant to the overall data architecture. While there is little actual data science at this stage, it provides the essential platform to pave the way for success in the rest of the book.

In this chapter, we will cover the following topics:

• Data management responsibilities
• Data architecture
• Companion tools