Azure Data Engineering by Diagram
A Visual Field Guide to Data Factory, the Data Lake and Production Pipelines
by Kapil Dev V
A visual field guide to building data pipelines on Azure. Thirty-five diagrams carry the explanation across twenty-eight chapters, from an empty subscription to a platform other people can depend on. One running case, a retailer's daily sales files, ends in a capstone you build and mark yourself.
The Kindle eBook. Amazon.in in India, Amazon.com outside India.
Inside the book
- Tenants, subscriptions and resource groups, and a practice subscription with a budget alert
- The storage account toggle that turns blob storage into a data lake, and access tiers
- Data Factory end to end: linked services, datasets, activities, pipelines, dependency conditions
- Integration runtimes, and why a correct pipeline cannot reach your database
- Managed identity, and pipelines that hold no credentials at all
- Metadata-driven loops: Get Metadata, Filter, ForEach, Switch, Validation
- Incremental loads: watermarks, change data capture, and backfills
- Schedule, tumbling window and storage event triggers, drawn on one timeline
- Databricks notebooks called from the factory, and Unity Catalog's access chain
- The star schema, Delta tables, MERGE, and serving the gold layer with Synapse SQL
Written for the engineer whose company just picked Azure, the analyst handed Data Factory, the candidate with an Azure data interview next week, and anyone who can build the thing but wants to be able to draw it.
