Introduction Ever wondered what happens behind the scenes when you drag a visual into Power BI? That’s DAX queries  at work. While most users write DAX formulas  to calculate measures or columns, DAX queries  go one level deeper — they let you directly query your model, test logic, and debug calculations.In this post, we’ll break down what DAX queries are, how they work, their structure, examples, pitfalls, and best practices — plus a few pro tricks to level up your Power BI

Overview When you connect Power Query / Power BI to a SharePoint site (or document library), there are (at least) two common M-functions you may see or use: SharePoint.Files(siteUrl as text, optional options as record) as table SharePoint.Contents(siteUrl as text, optional options as record) as table Although they sound similar, their behavior, performance, metadata returned, and navigation experience differ. Understanding their differences helps in building more robust and p

Hook:  If your model “mysteriously” changes numbers, breaks relationships, or sorts months alphabetically—blame data types. What we’ll cover:  where to define types (and why), the safest order of operations across the ETL chain, Power Query vs. Model vs. Table View, special cases (DirectQuery, currency, duration), and concrete, copy-paste examples. 1) Why data types matter (and where they live) Power Query (PQ):  Data shaping stage. Types here affect folding, transformations

If you’re already familiar with Power BI  and Power Automate , you know how powerful it is when these two tools work together. But one of the most game-changing triggers  in Power Automate is: 👉 “Run a query against a dataset” This trigger lets you execute DAX queries (Data Analysis Expressions)  directly against your Power BI dataset from a flow. That means you can extract aggregated results, row-level values, or KPIs in real time — and then use that information to trigger

Hook:  Hard-coded paths are silent project killers. Move a file, share a workbook, or publish a PBIX—and boom: refresh fails. Goal:  In ~10 minutes you’ll set up robust, parameter-driven paths for Excel (Power Query) and Power BI (Desktop & Service), plus a tiny, reusable M pattern you can paste into any project. 1) Why hard-coded paths fail When you embed "C:\Users\Alice\Project\data.csv" in a query, anyone whose files live elsewhere (e.g., D:\Work\Data\) will get errors. I

Processing invoices is one of the most common but also one of the most time-consuming tasks in any finance or business department. Manually typing invoice numbers, vendor names, or due dates into an ERP or Excel sheet not only takes time but is also error-prone. With Power Automate and AI Builder , you can automate this process: invoices get uploaded (or even received by email), an AI model extracts key information, and the results can be sent by email or stored in your syste