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A Metadata-driven Approach Enabling Real-time Data Analysis at Qrious

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Real-time updates with continuous data flow

Eliminated need for expensive migration projects

Dynamic SCDs improved data quality and accuracy

Challenge

Qrious needed to dynamically ingest data from multiple sources using a metadata-driven approach.

Solution

The team created a utility that utilized parameters and metadata stored in Snowflake and dynamically extracted and ingested data from various sources, including SQL Server and SharePoint.

The team eliminated the need for costly data migration processes, enabled regular data ingestion, including Change Data Capture, and the creation of dynamic SCDs.

Results

  • Substantial cost savings in data management operations- avoiding complex data migration.
  • Continuously extracting and ingesting data into target systems led to a smoother and more streamlined data pipeline.
  • Reduced downtime and quality assurance.
  • Creating dynamic Slowly Changing Dimensions (SCDs) has improved data quality and accuracy, ensuring Qrious maintains a comprehensive and reliable dataset for analytics.