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Most companies produce far more data than they can neatly model upfront: application events, device logs, search queries, database exports, images, audio, and documents. A data warehouse expects data to be cleaned and shaped into tables before it is loaded. A data lake takes the opposite approach. It stores everything in its original form first and lets teams decide how to use it later.

In this chapter, we will look at what a data lake is, how it stores and organizes raw data, how that data gets queried, and the problems that appear when a data lake isn't managed carefully.