Implementation of Metadata Pipeline from ADLS to Microsoft Fabric Lakehouse

About the Offering

The Metadata Pipeline is designed to incrementally load CSV files from Azure Data Lake Storage (ADLS) to Microsoft Fabric Lakehouse. The pipeline ensures efficient data ingestion, transformation, and automated monitoring while maintaining data consistency and minimizing downtime. This includes: Notebook Execution for reading and transforming CSV files. SQL Stored Procedure to manage incremental loading logic. Teams Notifications to track the pipeline execution status. Ensures consistency between source and Fabric Lakehouse tables. Sends real-time Success/Failure alerts to stakeholders via Teams messages.

Solution Approach

Reads CSV files from ADLS and applies transformations if needed. Writes data to Microsoft Fabric Lakehouse in an optimized format (Delta/Parquet). Handles incremental loading logic to avoid duplicates.

Why Quadrant

Quadrant Technologies employs a pioneering factory model with agile pods to develop industry-specific use cases. 

Our approach ensures efficient, governed data management and has proven success in regulated industries. 

We deliver tailored solutions that drive value realization and operational efficiency for enterprise businesses.

Business Impact

60% reduction in development effort, requiring minimal manual intervention

Automated Incremental Ingestion – Eliminates manual efforts by identifying and loading only new/updated data.

Optimized Storage – Converts CSV files into a structured format (Delta/Parquet) for efficient querying.

Real-time Monitoring – Teams notifications ensure execution tracking without manual intervention.

Scalable & Reliable – Supports large-scale data processing with high performance.