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Corso · 7 capitoli

Data Engineering with AI

The pipeline half of the data world: dbt models, orchestrated DAGs, quality gates, broken-pipeline debugging, and warehouse cost, with agents in every loop.

A pagamentopractitioner7 capitoli112 minInglese + 6 lingueCertificato al completamento
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Cosa saprai fare

  • Boot the Anchorwell data lab, a DuckDB warehouse with dbt and Dagster already running, and see how the path's six chapters connect before you touch your own stack.
  • The dbt workflow where an AI agent drafts and you decide what actually ships to production.
  • Write the pipeline spec, drive an agent to build the DAG, and harden it with the retries and idempotency it won't add on its own.
  • Turn an agent's noisy first-pass checks into the few that actually stop a bad load.
  • Drive an agent through Dagster's run history and check results to find, verify, and fix what actually broke.
  • Auto-generate column docs and lineage notes with an agent, review them like any other agent draft, then write down one metric definition everyone can point to.

Cosa contiene

  1. 1
    Data Engineering with AI: Start Here

    Boot the Anchorwell data lab, a DuckDB warehouse with dbt and Dagster already running, and see how the path's six chapters connect before you touch your own stack.

    10 min
  2. 2
    Agent-Assisted SQL & dbt Modeling

    The dbt workflow where an AI agent drafts and you decide what actually ships to production.

    18 min
  3. 3
    Pipelines by Spec: DAGs with Agents

    Write the pipeline spec, drive an agent to build the DAG, and harden it with the retries and idempotency it won't add on its own.

    15 min
  4. 4
    Data Quality as Code

    Turn an agent's noisy first-pass checks into the few that actually stop a bad load.

    17 min
  5. 5
    Debugging Broken Pipelines

    Drive an agent through Dagster's run history and check results to find, verify, and fix what actually broke.

    18 min
  6. 6
    Docs, Lineage & Definitions

    Auto-generate column docs and lineage notes with an agent, review them like any other agent draft, then write down one metric definition everyone can point to.

    16 min
  7. 7
    Warehouse Cost & Performance

    Triage a warehouse's query history with an agent, then prove one fix with real before and after numbers.

    18 min

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