Intake - taking the pain out of data access
summary
Intake provides a concrete claim: a single API that turns catalog entries into usable data with a one-liner .read returns a pandas DataFrame, backed by YAML catalogs that include metadata, user parameters and YAML catalogs with user parameters and built-in plots. The demo shows a Jupyter-widgets GUI, an Intake server for auth and monitoring, caching on first access, plugins for CSV, s3, GitHub issues, xarray and a Spark hook, and the examples run live.
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chapters (14)
- 0:00Intake introduction
- 1:25Traditional data loading problems
- 5:22How Intake simplifies access
- 6:27Data scientist workflow
- 7:53Data providers' role
- 10:02IT security and access
- 11:48Developers' perspective
- 14:18Live demo of Intake
- 16:44Intake GUI exploration
- 18:59Creating catalogs
- 23:16Intake drivers state
- 24:20Key features and ecosystem
- 25:48Call to action
- 26:38Q&A
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