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Most Power Query tutorials show you how to load data. This one shows you how to keep it historically accurate. Learn to implement Type 1, Type 2, and hybrid SCD strategies entirely in M — with complete, production-ready code patterns, change detection, surrogate key generation, and a hands-on exercise to cement the concepts.

Legacy flat files from mainframes, ERPs, and AS/400 systems don't cooperate with Power Query's default import wizard. This lesson teaches you how to parse fixed-width and non-standard delimited formats with full control — from raw binary loading to reusable, dynamic parsers.

The M standard library has over 700 built-in functions — and most Power Query users never get a proper map of the territory. This lesson teaches you how the library is organized by namespace, what each major namespace covers, and how to confidently look up and use any function you encounter.

Learn how to build reusable, refreshable data connections in Power Query — including how to connect to external Excel workbooks, named tables, and named ranges. This foundation lesson turns a two-hour monthly chore into a one-click refresh.

Native Query Diagnostics only goes so far. Learn how to build a full diagnostic harness directly in M that captures per-step execution time, row counts, and anomaly detection — giving you precise bottleneck identification in complex multi-step pipelines.

Most Power Query practitioners either don't know fuzzy matching exists or apply it naively and produce garbage results. This deep-dive lesson covers how the n-gram Jaccard engine actually works, how to build multi-field probabilistic scoring with blocking for scalability, and how to validate your results with precision and recall — so you can trust what comes out.

Generic date tables break when fiscal years, ISO week numbering, and holiday-aware working day calculations enter the picture. This lesson walks you through building a fully parameterized Power Query M function that handles all three — with production-ready code you can deploy today.

Learn how to build production-ready cross-tabulated reports entirely in Power Query. This lesson goes beyond the Pivot Column dialog to teach you how to pre-aggregate data, add dynamic totals rows and columns, enforce column order, and handle the edge cases that break most pivot implementations.

Most Power Query users never touch binary data — but when a legacy system or API throws raw bytes at you, the M language has everything you need to parse it. This lesson teaches you how to read binary files, decode typed values from byte positions, and build a complete parser that converts any structured binary format into a clean, queryable table.

Learn how to filter and sort rows in Power Query with genuine control — not just clicking dropdowns, but understanding the M code behind each step. This lesson uses a realistic sales dataset to teach text filters, date ranges, number conditions, multi-column sorting, and troubleshooting the mistakes that trip up beginners.

Stop letting schema drift silently corrupt your Power Query reports. Learn how to build a full validation and type enforcement pipeline in M that checks column presence, type compatibility, and nullability against an explicit contract — and tells you exactly what went wrong when it doesn't match. This is the data quality architecture your Power BI models have been missing.
Most analytics models quietly corrupt historical data by overwriting dimension attributes without any tracking strategy. This deep-dive lesson teaches you to implement both Type 1 (overwrite) and Type 2 (version) SCD merge patterns entirely in Power Query M, with complete code, realistic scenarios, and honest guidance on when the tool reaches its limits.