1261 in-depth articles — from Excel foundations to production machine learning. Filter by topic or difficulty to find exactly what you need.

Learn how to use Power Automate Desktop's clipboard actions to transfer data between Windows applications programmatically. This lesson covers Set Clipboard Text, Get Clipboard Text, keyboard simulation, timing issues, and building reliable multi-application data transfer flows from first principles.

Learn how to build self-referential parent-child hierarchies in Dataverse, configure hierarchical security so managers automatically inherit access to subordinates' records, set up multi-level rollup aggregation, and display interactive tree visualizations in model-driven apps. This expert-level lesson covers the architecture, edge cases, and performance trade-offs you need to get it right.

Learn how to build production-quality period comparison analysis in pandas using shift and pct_change. This lesson covers MoM, YoY, and rolling metrics for single and multi-segment time series, with realistic business data and a reusable report function you can ship immediately.

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.

Most RPA deployments fail not because the bots are bad, but because the orchestration layer wasn't designed for production. This expert lesson walks you through building a complete queue-driven, self-healing bot fleet using Power Automate Work Queues, machine groups, and layered monitoring cloud flows. You'll leave with a blueprint for 24/7 automation that recovers from failures automatically and scales without babysitting.

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 create new columns in pandas using np.where for conditional flags, pd.cut for numeric bucketing, and .map() for code-to-label substitution. Three essential tools that replace slow loops and Excel workarounds with fast, readable Python.

Standard lookups point to one table. But real business data is messier than that — a customer might be an Account or a Contact, an expense might belong to a Project or a Department. Learn how Dataverse polymorphic lookups, Customer columns, and Regarding columns solve this cleanly, and how to configure them end-to-end in model-driven apps.

Wide data is easy to read but hard to analyze. Long data is easy to analyze but hard to present. This lesson teaches you exactly when to use melt, pivot, and unstack in pandas — with realistic examples and a clear workflow for converting between formats.

Legacy systems don't give up their data easily — especially when they're running inside Citrix or IE. This lesson teaches you how to build Power Automate Desktop flows that reliably extract data from virtual environments using layered selector strategies, OCR, image recognition, and production-grade session management.

Virtual tables let you surface live data from SQL Server, REST APIs, and OData services directly inside your model-driven app — no ETL, no data copy, no sync. This lesson teaches you to configure OData data sources, map columns, build cross-system relationships, and handle the security and performance challenges that come with production virtual table deployments.

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.