Materialized Lake Views: A SQL-First Path to Microsoft Fabric

If you're running Microsoft Fabric and your team knows SQL better than Spark, this walkthrough is for you.

Materialized Lake Views let you persist a standard T-SQL view as a Delta table with a single setting, no Spark code required. In this demo, we build one from scratch using Timextender Data Integration: ingesting Business Central data, building a star schema, and turning a custom view into a fully materialized, pre-computed table inside Fabric.

We also clear up the confusion between table shortcuts, notebook views, and materialized views, and shows exactly when each one makes sense.

The core idea here matters beyond this one demo: your Fabric Lakehouse doesn't have to be a Spark-only environment. With Timextender Data Integration, you can build and orchestrate the entire pipeline in T-SQL, from ingestion through a governed, pre-computed model, and deploy it to Fabric without retraining your team.

Lead the AI Era with Trusted Data

• Book a demo to see how a unified, metadata-driven approach keeps definitions, lineage, and refresh behavior consistent across the Timextender Data Platform.
• How AI-ready is your data, really? Answer 8 questions. Get an instant score across the pillars that matter most for production AI — and find out exactly where your gaps are before your next project exposes them. Takes 3 minutes.