Introduction
Analytics and service lessons in data quality
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1. Project Introduction
Project scenario
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Codespaces and repository overview
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CLI and dbt docs
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Data infrastructure and reports
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The downstream data quality resolution process
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2. Bring on the Chaos
Challenge: Bring on the chaos
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Solution: Bring on the chaos
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3. Issue Scoping
Exercise: Issue scoping
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Exercise: Documenting the scope
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4. Issue Replication
Exercise: Issue replication
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Exercise: Documenting the replication
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5. Data Profiling
Exercise: Data profiling, part 1
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Exercise: Using lineage for profiling
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Exercise: Documenting the profiling plan
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6. Data Profiling Queries
Exercise: Data profiling with queries, part 2
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Exercise: Querying for discrepancies
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Exercise: Analyzing county data
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Exercise: Analyzing issuing agency data
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Exercise: Summarizing profiling findings
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7. Downstream Pipeline Investigation
Exercise: Downstream pipeline investigation
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Exercise: Identifying problematic business logic
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8. Implement the Fix (Tests)
Exercise: Implementing DQ fix tests, part 1
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Exercise: Creating and running DQ tests
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9. Implement the Fix (Code)
Exercise: Implementing the DQ fix, part 2
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Exercise: Applying the final code fix
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10. Stakeholder Communications
Stakeholder communications
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Summarizing findings with the SBAR method
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