Part 10/14:

• Insurance & Healthcare: Swiss Life used unified data sources to resolve inconsistencies across portals, creating a single, reliable view—crucial for customer trust and timely fraud detection.

From Data Ingestion to Analytics: The Full Cycle

The process begins with real-time data ingestion from diverse sources, followed by data transformation—either via built-in functions or custom SQL—culminating in data being stored in data lakes or warehouses. The system maintains detailed lineage and quality metadata via catalogs, empowering users to confidently access accurate, up-to-date data.

Once the data is prepared, it feeds into Business Intelligence tools like ClickSense or any other visualization platform, enabling insights, predictive analytics, and machine learning.