97 Things Every Data Engineer Should Know by Tobias Macey

Author:Tobias Macey [Macey, Tobias]
Language: eng
Format: epub, pdf
Publisher: O'Reilly Media
Published: 2021-03-30T00:00:00+00:00

1 This chapter is a subset of a broader list of “98 Things That Can Go Wrong in an ML Project.”

Six Dimensions for Picking an Analytical Data Warehouse

Gleb Mezhanskiy

The data warehouse (DWH) plays a central role in the data ecosystem. It is also often the most expensive piece of data infrastructure to replace, so it’s important to choose the right solution and one that can work well for at least seven years. Since analytics is used to power important business decisions, picking the wrong DWH is a sure way to create a costly bottleneck for your business.

In this chapter, I propose six dimensions for evaluating a data-warehousing solution for the following use cases:

Ingesting and storing all analytical data

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