Microsoft Fabric Projects

The project focuses on architecting and deploying a robust, fully automated process that loads the daily campaign performance CSV into a Microsoft Fabric Lakehouse without any manual intervention.

The project focuses on architecting and deploying a robust, single, intelligent pipeline that acts as an automated triage process for a messy data landing zone to identify and route known data files, and archive them upon success, and quarantine any unrecognised files to ensure a clean, auditable, and reliable ingestion process.

The project focuses on building a foundational analytics engine using PySpark, where a backlog of critical questions from HR, Finance, and executive leadership are answered using production-level PySpark code necessary to transform raw data into actionable intelligence.

The project focuses on architecting and deploying a robust, automated, and incremental pipeline that efficiently identifies and consolidates only the new log files each day into a single, queryable Delta Lake table in the Lakehouse.

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The project focuses on architecting and deploying DataFlow Gen2 to resolve the foundational data quality crisis by mandating the use of DataFlow Gen2 to build a robust, reusable pipeline to standardise and clean the data.​​

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The project focuses on building a Fabric Notebook solution that handles the Complex maths, cleans the bad data, and automatically secures the PII (Personally Identifiable Information) of the consumers

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