Snowflake Research and Integration

[vibhatha]

🚀 Roadmap: Building the OpenGIN Data Lake & Org Hierarchy

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Step 1. Foundation Setup (Weeks 1–2)

✅ Goal: Get a working mini data lake locally.

• Install MinIO (object store).
• Create buckets: bronze/, silver/, gold/.
• Install DuckDB + Iceberg plugins.
• Load 1 Gazette PDF + 1 CSV dataset → run bronze → silver → gold flow manually.
• Write first DuckDB query against gold table.

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Step 2. ETL Automation (Weeks 3–4)

✅ Goal: Automate Gazette → Metadata → Org Hierarchy pipeline.

• Deploy Airflow/Prefect locally.
• DAG: Gazette PDF → OCR → JSON → MinIO (silver) → Iceberg (gold).
• Log lineage with etl_job_id.
• Schedule pipeline to run daily.
• Document outputs in a simple data catalog (spreadsheet or OpenMetadata-lite).

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Step 3. Data Modeling (Weeks 5–6)

✅ Goal: Establish schemas for key gold tables.

• Finalize gazette_metadata table.
• Finalize org_hierarchy_versions table.
• Add statistics tables (e.g., tourism arrivals, foreign employment metrics).
• Define stable IDs for ministries/departments (to handle renames).

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Step 4. Integration with OpenGIN APIs (Weeks 7–8)

✅ Goal: Make gold data queryable through APIs & graph DB.

• Mirror org hierarchy snapshots into Neo4j.
• Expose /orgchart?date=YYYY-MM-DD endpoint in Nexoan Read API.
• Link gazette_id → Gazette PDF → Org Node in APIs.
• Add simple visualization UI (OpenGIN Viz).

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Step 5. Production Hardening (Weeks 9–12)

✅ Goal: Turn prototype into production-ready data lake.

• Move MinIO + Airflow to Choreo cloud (dev → staging → prod).
• Add Iceberg catalog (Hive Metastore or Glue).
• Introduce OpenMetadata for search, lineage, and governance.
• Add compaction jobs (clean up small files).
• Expand beyond gazettes: ingest tourism, employment, immigration datasets.

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Step 6. Snowflake Integration (Weeks 13+)

✅ Goal: Enable scalable analytics and external data sharing.

• Connect Snowflake external tables to Gold Iceberg datasets.
• Build BI dashboards (Tableau / PowerBI) on top of Snowflake.
• Allow secure data sharing with government agencies, researchers, and partners.
• Use Snowflake for cross-ministry analytics (e.g., tourism ↔ forex ↔ employment).
• Keep MinIO + Iceberg as source of truth; Snowflake is the analytics/sharing layer.

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Outcome (3+ months)

• Centralized Data Lake: all gazettes & ministry data stored raw + structured.
• Curated Gold Tables: gazette_metadata, org_hierarchy_versions, key stats.
• Automated Pipelines: Airflow DAGs keep data fresh.
• APIs & Graph Ready: Org structures queryable by date.
• Auditability: Every org change traceable to Gazette evidence.
• Analytics & Sharing: Snowflake enables dashboards and controlled data access for external stakeholders.

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👉 This roadmap now moves you from prototype → production → external analytics in ~16 weeks.
By the end, OpenGIN will have a credible, auditable, queryable, and shareable data backbone.

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Reference

Generated by a series of discussions @vibhatha had with ChatGPT.