41 in-depth articles — from Excel foundations to production machine learning. Filter by topic or difficulty to find exactly what you need.

Learn how to connect Power BI Desktop to a Fabric lakehouse SQL Analytics Endpoint, build a star schema with DAX measures, and publish a production-ready report — no Direct Lake required. This lesson explains every step from finding the connection string to scheduling refreshes, with clear guidance on when to use this approach over Direct Lake mode.

Learn the three essential write patterns for Delta tables in Microsoft Fabric: append, overwrite, and merge. This hands-on lesson teaches you exactly when to use each pattern — and how to avoid the silent data quality problems that come from choosing the wrong one.

Row-Level Security in Microsoft Fabric isn't just a T-SQL exercise — it's an architecture decision with serious implications for workspace roles, Power BI Direct Lake, and Spark access paths. This lesson walks through building dynamic RLS policies from scratch, understanding where the security envelope stops, and verifying your policies work as intended before real users hit production.

Learn how to define Power Query parameters in Dataflow Gen2 and pass runtime values from Fabric pipelines — building a single, reusable ingestion flow that adapts to different regions, time periods, or environments without duplicating logic. Includes a full hands-on exercise and troubleshooting guide.

Learn how to bulk-load Parquet and CSV files from OneLake into a Microsoft Fabric Warehouse using COPY INTO and the Pipeline Copy Activity. This hands-on lesson covers file path patterns, CSV configuration options, column mapping, and post-load verification — everything you need to run production-grade ingestion jobs.

Delta tables don't optimize themselves. Learn how V-Order encoding, file compaction with OPTIMIZE, multi-dimensional data skipping with Z-Order, and storage reclamation with VACUUM work together to make your Fabric Lakehouse queries dramatically faster and cheaper to store. This lesson goes deep into the internals so you know exactly when and why to apply each technique.

Full table loads don't scale — and sooner or later every production pipeline needs an incremental strategy. Learn how to build a complete watermark-based incremental load pattern in Microsoft Fabric using Lookup activities, parameterized Copy activities, and PySpark notebook watermark updates.

Every Fabric lakehouse comes with a built-in SQL interface that lets you run T-SQL against Delta tables — no warehouse required. Learn how to write queries, create views, join across tables, and connect from SSMS or Power BI, all against the same data your Spark notebooks write.

Direct Lake mode is Power BI's fastest connection strategy for Fabric lakehouses — but only if your Delta tables are structured correctly. This lesson teaches you how to create V-Ordered gold tables, manage framing, diagnose DirectQuery fallback, and keep your reports fresh without expensive import cycles.

Learn how to build a real PySpark notebook in Microsoft Fabric from scratch — reading CSV files from Lakehouse storage, cleaning and transforming data, and writing Delta tables that are immediately queryable via SQL. This hands-on lesson teaches Spark fundamentals in the context you'll actually use them.

Learn how to turn a basic Fabric pipeline into a production-grade, self-healing automation. This lesson covers schedule triggers, activity-level retry policies, workspace alerts, and custom email notifications with dynamic content — everything you need to stop monitoring pipelines manually.

When pipelines run slow or fail silently, you need more than hope — you need visibility. This lesson teaches you how to use the Fabric Monitoring Hub and Capacity Metrics app to track activity, diagnose failures, and understand what your workloads are actually costing your capacity.