
Worked on the microsoft/fabric-toolbox repository to deliver a Capacity ID Deduplication and Data Pipeline Enhancement feature aimed at improving the accuracy of capacity analytics and supporting calendar-based reporting. Leveraged PySpark, Delta Lake, and SQL to extract active capacity IDs from FUAM_Lakehouse.capacities, excluding those with SKU 'PP3', and ensured uniqueness to reduce data duplication. Updated the data pipeline to clean the silver table and aggregate timepoints for a new calendar table, enhancing data quality for downstream analytics and BI dashboards. The work focused on robust distinct extraction, streamlined data processing, and improved maintainability through clear, incremental code changes.
May 2025 — Microsoft Fabric Toolbox (microsoft/fabric-toolbox). Implemented Capacity ID Deduplication and Data Pipeline Enhancement to improve accuracy of capacity analytics and support new calendar-based reporting. Actions included extracting active capacity IDs from FUAM_Lakehouse.capacities, excluding SKU 'PP3', ensuring uniqueness, cleaning the silver table, and aggregating timepoints for a new calendar table. Commits: ecc5504167491717b86ccd9be0f2d4c25ada8afa (added distinct) and 4a863464469533245aff18f055debe777e2609e4 (fix for getting distinct capacity id list from FUAM_Lakehouse.capacities). This work reduces duplicates, enhances data quality, and enables more reliable downstream analytics and BI dashboards.
May 2025 — Microsoft Fabric Toolbox (microsoft/fabric-toolbox). Implemented Capacity ID Deduplication and Data Pipeline Enhancement to improve accuracy of capacity analytics and support new calendar-based reporting. Actions included extracting active capacity IDs from FUAM_Lakehouse.capacities, excluding SKU 'PP3', ensuring uniqueness, cleaning the silver table, and aggregating timepoints for a new calendar table. Commits: ecc5504167491717b86ccd9be0f2d4c25ada8afa (added distinct) and 4a863464469533245aff18f055debe777e2609e4 (fix for getting distinct capacity id list from FUAM_Lakehouse.capacities). This work reduces duplicates, enhances data quality, and enables more reliable downstream analytics and BI dashboards.

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