Data Warehouse - KeynesYouDigIt/Knowledge GitHub Wiki

DWs are central OLAP repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. Ideally, they are considered the single source of truth for a history of business operations. (This is often a asymptotic goal rather than a destination)[https://youtu.be/FvCInKiLJVg?t=388], as business needs and data keeps changing.

For SAAS companies this ideal is a bit easier of course, but I believe any most businesses can and should create a data warehouse.

Warehouses are schematized, which makes them more predictable and easy to read than Data Lakes (and of course, harder to write unstructured data to).

Tools for implementation

AWS Redshift, Aurora Postgres Postgres (just.... big) Teradata (Snowflake?? kinda??))

The Data bricks "lakehouse" - https://databricks.com/discover/data-lakes/introduction

See more at 1.3-Storage-and-retrieval#data-warehousing