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dataflow-gen2

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Retail & E-Commerce Sales Analysis built with Microsoft Fabric and Power BI. Includes Dataflow Gen2 ingestion, Lakehouse-based dbo/Silver/Gold layers, Fabric pipeline orchestration, semantic modeling, DAX, RLS, incremental refresh, scheduled refresh, and interactive business reporting.

  • Updated Mar 27, 2026
  • Jupyter Notebook

End-to-end data engineering pipeline on Microsoft Fabric: Incremental watermark ingestion implemented from MySQL, PostgreSQL & Google Sheets through Bronze/Silver/Gold medallion architecture to a star schema warehouse, through the Dataflow Gen2.

  • Updated Jun 27, 2026
  • Jupyter Notebook

End-to-end Microsoft Fabric data platform using Medallion Architecture, integrating ADLS Gen2, SQL Server and GitHub. Implements metadata-driven ingestion, PySpark, Dataflow Gen2, incremental loading, data cleansing and a Gold star schema, exposed through Direct Lake for Power BI reporting.

  • Updated Sep 22, 2026
  • Jupyter Notebook

End-to-end banking analytics platform (SQL Server → Fabric → Power BI) processing 49,615+ transactions worth ₹302M across 10,000 customers with 10 SQL-driven insights powering cross-sell, failure detection, and branch prioritization.

  • Updated Sep 25, 2026
  • TSQL

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