data lake
Retain diverse data for later processing and analysis with governance.
Use this when You need to preserve raw events and files for several future analytical uses.
without the term
“Keep raw events and files for future analysis, with enough metadata and access rules to make them usable.”
with the term · How do you ask a model for data lake?
Design this data lake’s layout, catalogue, access controls, and retention. Verify one consumer query against source records.
What is data lake?
A data lake stores data in varied formats, often on object storage, so consumers can process it for different purposes. Catalogues, access control, quality, and retention determine whether the stored data is usable.
Why does data lake matter when vibe coding?
An agent can dump files into buckets without a discoverable schema or deletion policy.
How do you do data lake?
Define ownership, formats, metadata, partitions, permissions, and retention. Verify a consumer can discover, read, and reconcile a sample dataset.
What goes wrong with data lake?
A lake is not inherently schema-free or transaction-free; table formats and lakehouse systems can add transaction semantics.
Sources for this entry
- AWS: Data lakes
A lake retains data in varied formats for later processing and analysis; governance and discoverability still matter.
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