Power BI last year compares the wrong weekday? (Tiny Fix 8)
If your last-year measure uses SAMEPERIODLASTYEAR on a date column, Power BI compares each day with the same date last year, not the same weekday. 7 March 2026 is a Saturday, but 7 March 2025 was a Friday, so every day is compared with the wrong weekday. The recommended way is calendar-based time intelligence (preview). A calendar compares by week, so the Saturday of week 10 meets last year's week 10 Saturday: File, Options and settings, Options, Preview features: select Enhanced DAX Time Intelligence, then restart Power BI Desktop. In the Data pane, right-click your Date table, then Calendar options, New calendar. Year = Week Year, Week = Week, Date = Date. Validate data, then Save and close. Point every last-year measure at the calendar: SAMEPERIODLASTYEAR ( 'Retail weeks' ) Check: before, Saturday +127% and Monday -50%. After, every day lands between +7% and +15%, and the bars line up. Trap from my test: start the date table on the Monday that begins week 1 (30 Dec 2024 for 2025). Mine started on 1 January and every comparison slipped by two days. Calendars don't work with live connected or composite models yet. Microsoft Learn: https://learn.microsoft.com/power-bi/transform-model/desktop-time-intelligenceWhy does my Power BI slicer show items with no data? (Tiny Fix 7)
Pick North in a Region slicer and the Product slicer still lists all 10 products, even the 4 that North never sold. Why: a slicer lists every value in its own table, and the relationships filter one way, into Sales, never back. Microsoft advises against switching the relationship to Both for this. Filter the slicer instead: Click the Product slicer and open the Filters pane. Drag your measure (Total sales) into Filters on this visual. Under Show items when the value, pick is not blank, then Apply filter. Check: before, 10 products. After, only the 6 that North sold. Microsoft guidance: learn.microsoft.com/power-bi/guidance/relationships-bidirectional-filtering
Power BI DAX Financial Functions Explained | RATE, INTRATE & RECEIVED
In this video, you'll learn three important Financial DAX Functions in Power BI with practical business examples and step-by-step demonstrations. ✅ RATE Function – Calculate interest rates for loans and annuities ✅ INTRATE Function – Determine the interest rate earned on fully invested securities ✅ RECEIVED Function – Calculate the maturity value received from discounted securities watch?v=WDwYz-oGcV4?si=7sO1r1A0F9y05Rz4TBILLPRICE, TBILLYIELD & TBILLEQ in Power BI DAX | Financial DAX Functions Explained
In this video, you'll learn three important Financial DAX Functions in Power BI: ✅ TBILLPRICE ✅ TBILLYIELD ✅ TBILLEQ Using practical business and finance scenarios, I explain how these functions help calculate Treasury Bill prices, yields, and bond-equivalent yields directly within Power BI. Whether you're a Power BI Developer, Data Analyst, Financial Analyst, or someone preparing for Microsoft Power BI interviews, this tutorial will help you understand these financial functions with ease.Power BI Financial DAX Functions Explained | ODDFPRICE, ODDFYIELD, ODDLPRICE & ODDLYIELD
In this video, you'll learn four advanced Financial DAX Functions with practical, real-time business examples. ✅ ODDFPRICE ✅ ODDFYIELD ✅ ODDLPRICE ✅ ODDLYIELD If you find this video helpful, please Like, Share, and Subscribe to the NDAC Channel for more learning content.MDURATION, PDURATION & NPER in DAX | Financial Functions with Real-Time Examples
In this Power BI DAX tutorial, learn how to use MDURATION, PDURATION, and NPER financial functions with practical real-world examples. Whether you're preparing for Power BI interviews, working in financial analytics, or improving your DAX skills, this video will help you understand these advanced financial DAX functions clearly. Subscribe for more Power BI, DAX, Microsoft Fabric, Data Analytics, and Business Intelligence tutorials.Claude Built My Power BI Dashboard. Here's how.
I sketched a rough wireframe of a dashboard I wanted—no DAX, no data model, just a layout idea. Then I handed it to Claude AI connected to Power BI Desktop through MCP and watched it build the actual dashboard: creating the semantic model, writing every measure from scratch, and turning a static sketch into a working, interactive report. This is the wireframe-to-dashboard workflow in full — how Claude reads a visual mockup, maps it to real fields and calculations, and produces DAX measures on its own without me writing a single line.Stop Documenting Power BI Manually: 5 Claude AI Hacks
Claude AI + Power BI (via MCP) Claude AI can now: Read your Power BI semantic model Audit your DAX Create new measures Query your data live ⚡ In this video: the 5 highest‑value things to do right after connecting Claude to Power BI, demonstrated on a real, messy, production‑style model. You’ll see Claude: Auto‑document an entire model in ~90 seconds Catch real DAX errors (divide‑by‑zero, duplicated measures) Write and insert a Sales YoY Growth % measure with proper blank‑handling Answer data questions with live DAX queries—no visuals needed Flag relationship problems that silently produce wrong results 👉 Which one are you trying first? watch?v=V-1er3Q_lrQHybrid Tables in Power BI | Shabnam Watson
Hybrid Tables in Power BI Hybrid tables, a new addition to Power BI, are a game changer in that they provide the best of both worlds by allowing one table to have two storage modes at the same time! Before the introduction of Hybrid tables, each table in Power BI could only have one storage mode: Import which loaded data entirely into Power BI’s memory or DirectQuery which left data in the back-end data source. When working with near real time requirements, Power BI developers had to use tables with DirectQuery; however, DirectQuery by itself could result in less than optimum query performance for large datasets and put a burden on the backend system. Hybrid tables combine the two storage modes and therefore provide improved query performance for historical data by loading them into memory (Import) and provide near real time capability for recent data (DirectQuery). Join this session to learn about different table storage modes in Power BI including the newest Hybrid option and how to use it. Agenda: Introductions (5 mins) Presentation (55 mins) Q&A session (15 mins) About Shabnam Watson: Shabnam Watson is a Business Intelligence consultant and Microsoft Data Platform MVP with 20 years of experience developing Data Warehouse and Business Intelligence solutions. She has worked across several industries including Supply Chain, Finance, Retail, Insurance, and Health Care. Her areas of interest include Power BI, Analysis Services, Performance Tuning, PowerShell, DevOps, Azure, Natural Language Processing, and AI. Her work focus within the Microsoft BI Stack has been on Analysis Services and Power BI. She is a regular speaker and volunteer at national and local user groups and conferences. She holds a bachelor’s degree in Computer Engineering, a master’s degree in Computer Science, and a Certified Business Intelligence Professional (CBIP) certification by The Data Warehouse Institute (TDWI). This event is online. You may need to install Zoom: https://zoom.us/download Space is limited so reserve your seat. Contact with Shabnam: LinkedIn: https://www.linkedin.com/in/shabnamwatson/ www: https://shabnamwatson.wpcomstaging.com/ Twitter: shbwatson Members participating in Meetup Live events must be respectful in interactions with people and in content posted on the platform.
