37 lines
1.2 KiB
Markdown
37 lines
1.2 KiB
Markdown
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# Sprint 72 Plan: Data Engineering and Analytics Semantics Pack
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## Context
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Data workflows rely on schema, lineage, and transformation guarantees.
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Sprint 72 adds semantics for ETL/analytics/transformation-heavy systems.
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---
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## Goals
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1. Model dataset schema + lineage semantics
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2. Preserve transformation intent across language and engine changes
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3. Add data quality checks to migration acceptance
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4. Support reproducible data pipeline transpilation audits
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---
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## Steps
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### Step 949: Data lineage canonical model (12 tests)
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### Step 950: Transformation intent packet schema (10 tests)
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### Step 951: Schema evolution compatibility checker (10 tests)
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### Step 952: Deterministic data-sample replay runner (10 tests)
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### Step 953: Aggregation/window semantics preservation checks (10 tests)
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### Step 954: Data quality gate integration (8 tests)
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### Step 955: `whetstone_analyze_data_pipeline_semantics` MCP tool (8 tests)
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### Step 956: `whetstone_verify_data_pipeline_migration` MCP tool (8 tests)
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### Step 957: Analytics migration dossier template (8 tests)
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### Step 958: Sprint 72 integration summary + regression (8 tests)
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---
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## Quality Rule
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- Schema or lineage uncertainty requires explicit reviewer sign-off.
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