Architecting Data and Machine Learning Platforms

Chapter 6. Innovating with an Enterprise Data Warehouse

In Chapter 3, you learned that the choice between a data lake and a data warehouse as the central component of your cloud data platform comes down to whether your organization is engineering/science-first (choose a data lake) or analytics-first (choose a DWH). In Chapter 5, we focused on the concept of data lake as a central element in the design of a data platform. In this chapter, you will learn how to address the same problems of cost, democratization, flexibility, and governance using a modern data warehouse as the central element instead.

We will start with a quick recap of the problems being addressed by building a data platform and discuss the technology trends that make a cloud DWH an appealing solution. Then we will do a deep dive into what a modern DWH architecture looks like and how you can effectively enable data analysts and data scientists with it.

A Modern Data Platform

Whenever you undertake a large technology project, you should first ask yourself what business goals are you trying to accomplish, what are your current technology challenges, and what technology trends do you want to leverage. In this section we will focus on helping you understand how to address these questions when building a modern data platform and how an enterprise DWH approach can steer the focus in your data platform design. Many of these concepts have already been touched on in the previous chapters, but it is useful to reframe them ...