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Power BI Guides & Tutorials
Master Power BI — DAX, Power Query, data modeling, dashboard design, deployment and the interview questions employers ask.
Power BI articles
Time Intelligence in DAX: YTD, MTD and Comparisons
DAX time intelligence for Power BI: the date table it depends on, year-to-date and month-to-date measures, fiscal year ends, prior-year comparisons with SAMEPERIODLASTYEAR and DATEADD, rolling windows with DATESINPERIOD, and the partial-month trap that turned a 62.7% increase into an 8.6% fall, shown with real numbers.
Power BI Gateway Explained: Connecting On-Prem Data
The Power BI data gateway explained: how it connects cloud reports to data on your own network using only outbound connections, when you need one, the standard, personal and virtual network gateways, where to install it and what machine it needs, clusters for high availability, its limits, and keeping it updated.
Power BI vs Excel: When to Use Each Tool
A task-by-task guide to choosing between Power BI and Excel at work: the signs a workbook has outgrown Excel, what Excel still does better, the worksheet row limit tested on a real two-sheet retail dataset, and the ways the two tools work together, from Power Query to Analyze in Excel and connected tables.
Power BI Tooltips: Adding Context to Visuals
How to use the three kinds of Power BI tooltip to add context without clutter: tooltip fields and aggregations, sentence-format templates, drill actions in the footer, report page tooltips built and assigned step by step, how line charts and cross-highlighting affect them, accessibility limits, and design tips.
Power BI Dataflows Explained for Beginners
Power BI dataflows for beginners: what a dataflow is, why Microsoft calls Gen1 legacy and recommends Dataflow Gen2 where Fabric is available, the problems dataflows solve, from reusable preparation to protecting sources, when not to use one, how to create and refresh one, and design habits that keep them useful.
Power BI Performance Tuning: Make Reports Faster
A method for making Power BI reports faster: measure first with Performance Analyzer and read its DAX query, visual display and other timings, then shrink the import model, reduce column cardinality on a real retail dataset, write lighter DAX, filter and simplify pages, and check capacity and gateways.