data lake

Data Lake

A storage system that holds raw data of any shape — structured tables, JSON, logs, images — without forcing it into a schema first.

When you'd see it: Cloud storage buckets — S3, Azure Blob, Google Cloud Storage — are the substrate. Lakes show up wherever data volume, variety, or messiness makes a traditional warehouse painful: clickstream logs, IoT sensor data, raw API dumps, files the data team hasn't gotten around to modeling yet.

Why it matters: The warehouse asks "what shape is this data?" before it can store anything. The lake says "dump it in, figure the shape out later." That flexibility is the whole appeal — and the whole risk. Lakes scale cheaply and accept anything; without discipline they become "data swamps" where nobody knows what's in there.

Common mistakes: Treating the lake as a substitute for the warehouse. They are complements. Raw data lands in the lake; cleaned, modeled data lives in the warehouse for analysts to query. Skipping the modeling step is how a lake stops being useful.

Related JSON, ETL