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reza.radacad.powerbi.data.ai

Reza Rad
#PowerBI, #MicrosoftFabric & #AI Tips
Helping you to utilize Data & AI
Author, Speaker & Consultant
Microsoft Regional Director & MVP

What Is Fabric IQ? โ€” The Context Layer AI Agents What Is Fabric IQ? โ€” The Context Layer AI Agents Actually Need

๐Ÿ”ฅ Just published โ€” a short clip from my Fabric Insider Ep. 6 interview with Yitzhak Kesselman, Corporate Vice President for Real-Time Intelligence at Microsoft Fabric.

AI agents need context โ€” the same way you do. As an employee, you have Outlook, Teams, documents, CRM, ERP. That context makes you productive. AI agents need the same thing.

Microsoft's answer โ€” a three-layer stack:

๐Ÿง  Work IQ โ€” who's your manager, your team, what you have access to

 ๐Ÿ“„ Foundry IQ โ€” documents, operational procedures, unstructured data

 ๐Ÿ—๏ธ Fabric IQ โ€” how your business actually operates. Structured data, streaming data, operational systems, connected.

And Fabric IQ itself has three layers โ€” OneLake data, semantic models (20+ million worldwide), and ontologies โ€” geospatial data, time series, actions, relationships with real business meaning.

This is the context layer that makes AI agents useful for running a business, not just answering questions about it.

Short clip in the comments ๐Ÿ‘‡

#MicrosoftFabric #FabricIQ #WorkIQ #FoundryIQ #AIAgents #FabricInsider #SemanticModel #OneLake #DataEngineering #FabricAnalytics #BusinessIntelligence #YitzhakKesselman #AgenticAI #Ontology #FabricUpdates
User-Context-Aware Calculated Columns โ€” Be Aware User-Context-Aware Calculated Columns โ€” Be Aware of This Before You Use Them

๐Ÿ”ฅ Just published โ€” a short video with one important warning.

They are calculated on the fly. Not pre-calculated like a traditional calculated column. Something between a calculated column and a measure.

โš ๏ธ Do not put heavy calculations inside them.

But used correctly โ€” beyond multilingual reports โ€” think RLS personalisation, translation, user-specific formatting. Fantastic when used right.

Short video in the comments ๐Ÿ‘‡

#PowerBI #CalculatedColumns #UserContext #PowerBITips #MicrosoftFabric #SemanticModel #PowerBIDeveloper #DAX #USERCULTURE #PowerBIDesktop #FabricAnalytics #PowerBIPerformance #DataModeling #BusinessIntelligence #PowerBIBestPractices
Career tip for recent graduates trying to break in Career tip for recent graduates trying to break into tech: go to local meetups. Attend in-person events.
It costs nothing. And it can change your career trajectory more than any job application.
You do not need to be an expert to show up. You need to show up to become one.

#CareerAdvice #TechCareers #NewGraduates #Networking #Meetups DataCommunity PowerBI MicrosoftFabric CareerTips TechIndustry JobSearch ProfessionalDevelopment RADACAD GrowthMindset CommunityBuilding
Heavy girl ๐Ÿ˜…๐Ÿ˜… 27kg #Akita #JapaneseAkita #do Heavy girl ๐Ÿ˜…๐Ÿ˜…
27kg
#Akita #JapaneseAkita #dog
๐…๐š๐›๐ซ๐ข๐œ ๐‚๐จ๐ซ๐ž ๐Œ๐‚ ๐…๐š๐›๐ซ๐ข๐œ ๐‚๐จ๐ซ๐ž ๐Œ๐‚๐ ๐’๐ž๐ซ๐ฏ๐ž๐ซ โ€” ๐ˆ๐ง๐ฌ๐ญ๐š๐ฅ๐ฅ & ๐Œ๐š๐ง๐š๐ ๐ž ๐Ž๐ง๐ž๐‹๐š๐ค๐ž ๐’๐ž๐œ๐ฎ๐ซ๐ข๐ญ๐ฒ ๐ฐ๐ข๐ญ๐ก ๐€๐ˆ ๐๐ซ๐จ๐ฆ๐ฉ๐ญ๐ฌ

๐Ÿ”ฅ Just published โ€” no code, no clicking through the portal. Just prompts.

Watch what happens when GitHub Copilot connects to the Fabric Core MCP Server:

๐Ÿ“‹ List every Fabric workspace in your tenant โ€” one prompt

 ๐Ÿ” Find which workspaces have custom OneLake Security roles configured โ€” one prompt

 โž• Create a new OneLake Security role โ€” one prompt, no code

 โœ๏ธ Edit an existing role โ€” one prompt

OneLake Security governance across dozens or hundreds of workspaces used to mean manually navigating the portal, workspace by workspace. Now it's a conversation.

In this video, I show what the Fabric Core MCP Server is, how to install it in VS Code, and a full live demo of everything above.

Video in the comments ๐Ÿ‘‡

#MicrosoftFabric #FabricMCP #MCPServer #OneLakeSecurity #GitHubCopilot #AIAgents #VSCode #FabricAdmin #DataGovernance #FabricAnalytics #NoCode #AgenticAI #DataSecurity #BusinessIntelligence #FabricDeveloper
What Is a User-Context-Aware Calculated Column in What Is a User-Context-Aware Calculated Column in Power BI?

๐Ÿ”ฅ Just published โ€” a short video explaining exactly what this is.

Calculated columns have always been static. Evaluated once, at refresh. Same value for every user. That has changed.

Here is what makes it different:

๐Ÿงฎ New Expression Context property โ€” Standard vs User Context

 โŒ Why USERCULTURE() used to throw an error inside a standard calculated column

 โœ… How this new type of calculated column evaluates โ€” not pre-calculated like a traditional one, not exactly a measure either. Something in between.

 ๐ŸŒ Opens the door to multilingual reports, RLS personalisation, and user-specific formatting โ€” all from a single semantic model

One of the most interesting additions to Power BI semantic modeling this year.

Short video in the comments ๐Ÿ‘‡

#PowerBI #CalculatedColumns #UserContext #PowerBITips #MicrosoftFabric #SemanticModel #PowerBIDeveloper #DAX #USERCULTURE #PowerBIDesktop #FabricAnalytics #Multilingual #ExpressionContext #PowerBIModeling #BusinessIntelligence
You see the MVP award renewal announcements. Years You see the MVP award renewal announcements. Years in the program. Community leadership. Books authored. YouTube channels with thousands of subscribers.

You don't see the first day.

You don't see the path it took to get there. The struggles. The effort. The years of quiet, unglamorous work before any of it was visible.

And that is exactly what you should see.

This is me. 2005. 21 years ago. No MVP award. No YouTube channel. No books written. Just someone spending time on MSDN forums, answering questions about SSIS โ€” because I loved doing it, not because I was building toward anything.

I did not know that day would eventually lead here. I just kept showing up.

Here is the lesson: everyone has a starting point. The person you look up to today had one too. Do not compare your current step to someone else's step 20 years down the road. That is not a fair comparison โ€” it never was.

Be yourself. Follow your own path. Build it one step at a time.

We all started somewhere.

#MVPBuzz #MicrosoftMVP #PowerBI #MicrosoftFabric #DataCommunity #Motivation #GrowthMindset #CareerJourney #NeverGiveUp #StartWhereYouAre #TechCommunity #PersonalDevelopment #RADACAD #Leadership #ThrowbackThursday
User Context Aware Calculated Columns in Power BI User Context Aware Calculated Columns in Power BI โ€” Multilingual Reports Made Simple.

๐Ÿ”ฅ Just published โ€” a short clip from my Fabric Insider Ep. 5 interview with Christian Wade โ€” Principal PM Architect for Power BI Semantic Models at Microsoft.

Calculated columns have always been evaluated at refresh time. Same value for every user. USERCULTURE() inside a calculated column never made sense โ€” because it would return the same locale for everyone regardless of who was logged in.

That has changed.

The new Expression Context property โ€” Standard vs User Context โ€” makes calculated columns user-aware. Evaluated at query time. Per user. Based on who is logged in.

A French user sees French product names. A US user sees English. Same model. Same data. Different experience per user โ€” automatically.

In the demo โ€” Christian adds ?language=fr to the URL. The entire report switches to French. Field list. Product names. Everything. No separate report. No separate model. One semantic model serving every language.

This completes the full multilingual stack:
โœ… Data translations โ€” user context aware calculated columns
โœ… Metadata translations โ€” table names, column names, measure names
โœ… Format string conversion โ€” currency and number formatting per locale

Short clip in the comments ๐Ÿ‘‡

#PowerBI #CalculatedColumns #UserContext #Multilingual #PowerBITips #MicrosoftFabric #SemanticModel #FabricInsider #ChristianWade #PowerBIDeveloper #DAX #USERCULTURE #PowerBIDesktop #FabricAnalytics #MultilingualPowerBI
Defining RLS in multiple places? SQL endpoint. War Defining RLS in multiple places? SQL endpoint. Warehouse. Lakehouse. Semantic model.

There is a better way.

Define security once in OneLake. Every workload observes it โ€” SQL, Spark, Semantic Model, Direct Lake, AI agents. One place. Everywhere.

๐Ÿ”ฅ Just published โ€” full step-by-step setup ๐Ÿ‘‡

๐Ÿ“บ https://youtu.be/d0BGZymdTxY

#MicrosoftFabric #OneLake #OneLakeSecurity #RLS #DataGovernance #DataSecurity #PowerBI #SemanticModel #DirectLake #DataEngineering #FabricAdmin #BusinessIntelligence #UserIdentityMode #FabricAnalytics #RowLevelSecurity
Defining security in every layer of your Fabric ar Defining security in every layer of your Fabric architecture โ€” warehouse, lakehouse, semantic model โ€” separately. Every time. For every workload.

That was the old way. OneLake Security changes it.

Define your security rules once in OneLake. Every workload observes them automatically. Spark notebooks. SQL analytics endpoint. Semantic models. Direct Lake. AI data agents. All of it.

One definition. Universal enforcement.

Short clip from my Fabric Insider Ep. 5 interview with Christian Wade โ€” Principal PM Architect for Power BI Semantic Models at Microsoft โ€” in the comments ๐Ÿ‘‡

#MicrosoftFabric #OneLake #OneLakeSecurity #DataGovernance #FabricInsider #SemanticModel #DirectLake #PowerBI #DataEngineering #FabricAnalytics #DataSecurity #DataPlatform #BusinessIntelligence #ChristianWade #PowerBIDeveloper
This is what our Auckland Power BI and Fabric comm This is what our Auckland Power BI and Fabric community looks like in person. ๐Ÿ‡ณ๐Ÿ‡ฟ

Great night. Great people. Great conversations.

We run regular in-person and hybrid sessions โ€” Power BI updates, Fabric deep dives, lightning talks from practitioners, and plenty of networking.

3,800+ members and growing. Come join us ๐Ÿ‘‡

#PowerBI #MicrosoftFabric #Auckland #NewZealand #DataCommunity #PowerBICommunity #RADACAD #UserGroup
60,000 ๐ฌ๐ฎ๐›๐ฌ๐œ๐ซ๐ข๐›๐ž๐ซ๐ฌ ๐จ๐ง ๐˜๐จ๐ฎ๐“๐ฎ๐›๐ž. ๐ŸŽ‰

I honestly did not expect to be writing this post today. But here we are โ€” 18th of July 2026 โ€” and the RADACAD YouTube channel just crossed 60,000 subscribers.

To every single one of you โ€” thank you. I read your comments. Every one of them. The questions, the feedback, the "this helped me so much", the "I have been following you since 2015" โ€” all of it. You have no idea how much it means and how much it motivates me to keep going.

This channel started as a place to share what I know about Power BI. It has grown into something I am genuinely proud of โ€” Fabric Insider interviews with Microsoft product team members, no-code AI demos, tutorials, shorts, community sessions. And there is so much more coming.

If you are not subscribed yet โ€” come join us. Every week there is new content on Microsoft Fabric, Power BI, and AI. Link to the channel in the comments ๐Ÿ‘‡

And to the 60,000 of you already there โ€” thank you. You are the reason I keep doing what I love. ๐Ÿ™

#YouTube #60KSubscribers #PowerBI #MicrosoftFabric #RADACAD #ThankYou #DataCommunity #YouTubeChannel #FabricAnalytics #DataEngineering #BusinessIntelligence #PowerBITips #AIAgents #FabricInsider #Grateful
Is AI going to take your job in data and analytics Is AI going to take your job in data and analytics?

Honest answer: it depends on what you do next.

AI is already building Dataflows, semantic models, Power BI reports, and documentation โ€” from prompts. That part is real.

But the professionals who learn agentic development, MCP Servers like Fabric MCP and Power BI Modeling MCP, and Fabric Skills โ€” they are not being replaced. They are doing in minutes what used to take hours.

The shift is not AI vs. you. It is AI-enabled you vs. the version of you that ignored the shift.

more links in the comments ๐Ÿ‘‡

#AIJobs #FutureOfWork #AgenticAI #MCPServer #FabricSkills PowerBI MicrosoftFabric GitHubCopilot DataEngineering FabricAnalytics PowerBIDeveloper AITools DataAnalytics CareerAdvice NoCodePowerBI
๐๐ž๐Ÿ๐จ๐ซ๐ž ๐ฒ๐จ๐ฎ ๐ฅ๐ž๐š ๐๐ž๐Ÿ๐จ๐ซ๐ž ๐ฒ๐จ๐ฎ ๐ฅ๐ž๐š๐ซ๐ง ๐‚๐€๐‹๐‚๐”๐‹๐€๐“๐„. ๐๐ž๐Ÿ๐จ๐ซ๐ž ๐ฒ๐จ๐ฎ ๐ฅ๐ž๐š๐ซ๐ง ๐’๐”๐Œ๐—. ๐๐ž๐Ÿ๐จ๐ซ๐ž ๐ฒ๐จ๐ฎ ๐ฅ๐ž๐š๐ซ๐ง ๐ญ๐ข๐ฆ๐ž ๐ข๐ง๐ญ๐ž๐ฅ๐ฅ๐ข๐ ๐ž๐ง๐œ๐ž. ๐‹๐ž๐š๐ซ๐ง ๐ญ๐ก๐ž ๐›๐š๐ฌ๐ข๐œ๐ฌ ๐จ๐Ÿ ๐ก๐จ๐ฐ ๐ƒ๐€๐— ๐š๐œ๐ญ๐ฎ๐š๐ฅ๐ฅ๐ฒ ๐ฐ๐จ๐ซ๐ค๐ฌ.

Most people jump straight to functions. That is why their DAX breaks in ways they don't understand.

Here is what you need to know first โ€” swipe through the carousel ๐Ÿ‘‰

๐Ÿงฎ The three types of DAX calculations โ€” Calculated Column, Measure, Calculated Table
 ๐Ÿ”— How to reference columns and tables correctly โ€” the syntax that everything else depends on
 ๐Ÿ”ข All the operators in DAX โ€” arithmetic, comparison, text, logical, and the IN operator
 ๐Ÿ“ฆ Variables โ€” VAR and RETURN โ€” the single biggest improvement to your DAX readability and performance
 ๐Ÿ’ฌ Comments in DAX โ€” because future you will thank past you
 ๐Ÿ“‹ Scalar vs Tabular functions โ€” know which one returns what before you use it
 ๐Ÿ—‚๏ธ All 10 DAX function categories โ€” know the landscape before you dive in

comments DAX to receive the link to the article ๐Ÿ‘‡

#PowerBI #DAX #DAXBasics #PowerBITips #MicrosoftFabric #DAXFunctions #PowerBIDeveloper #DataAnalytics #BusinessIntelligence #DAXCalculations #SemanticModel #PowerBIDesktop #PowerBITraining #RADACAD #BeginnerDAX
Lucy loves the morning walks 6km return To the wa Lucy loves the morning walks 
6km return
To the water and back home
#Akita #JapaneseAkita #walking #hiking #dogsofinstagram
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