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Hands On Tutorials to Implement Concepts

The best engineers have a strong appreciation for the pros and cons of a solution. 

With each exercise below we train the reflection muscle to further connect the dots. 

Data Pipelines:

  • DP001: Simple End-to-End Pipeline: Orchestrated HTTP → Warehouse → Semantic Model with success-gated refresh.

  • DP002: IoT Project: Built Bronze/Silver tables; applied Dataflow & Notebook transforms; added lineage + Fahrenheit conversion.

  • DP003: Metadata-Driven Pipelines: Scaled to 4 datasets using For Each loops and dynamic content.

  • DP004: Data Structures (Arrays): Learned to parse JSON arrays for dynamic pipeline control, including iteration over multiple sources.

  • DP005: Parameter Play: Implemented end-to-end parameterization across parent/child pipelines, notebooks, and stored procedures.

  • ​DP006: Data Quality Testing (Task 1): Enforced column-contract validation with auto-quarantine on schema drift. *

  • DP007: Data Structures (Objects): Focused on JSON objects-accessing key/value pairs and passing them into parameters/activities.

  • DP008: Data Structures (Advanced): Tackled nested arrays & objects; combined parsing patterns to handle real-world JSON payloads.

  • DP009: Data Quality Testing (Task 2): Centralized DQ rules in Warehouse metadata and processed multiple files dynamically. *

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