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feat: phase1-4 upgrade — BigQuery, Airflow, Looker Studio, 100/100 dbt tests - #2
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…incremental fact_orders, is_current_flag pattern
…y.py, 100/100 tests passing
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What this adds
Phase 1 — dbt upgrade: seller SCD2, dim_campaign, fact_seller_daily, incremental fact_orders, is_current_flag pattern. 100/100 tests on DuckDB.
Phase 2 — BigQuery: full adapter swap, target-conditional SQL (DuckDB + BigQuery parity), load_bigquery.py, 100/100 tests on Google Cloud.
Phase 3 — Airflow: daily DAG with source freshness check, BQ load, dbt build, branching logic (fresh/stale), retry handling.
Phase 4 — Looker Studio: live dashboard connected to BigQuery marts. Daily revenue, revenue by status, revenue by platform, total GMV scorecard.
Live dashboard: https://datastudio.google.com/reporting/cd32c187-2909-4b3e-8456-19d2efd0b275