Meet the judges of our May dataviz contest!

A Loan Calculator in Power BI allows users to explore different loan scenarios by adjusting key inputs such as loan amount, interest rate, and loan term. By using What-If Parameters, users can instantly see how changes affect monthly payments and total repayment amounts, enabling dynamic decision-making and clear financial insights—all in an interactive report environment.

You can find the data source file, along with Power BI files containing both solutions and those without, at the following link:

Study Materials 

Power BI in Fabric provides developers with multiple options for selecting a semantic layer. Various considerations can help you choose the appropriate semantic modelling strategy to meet your business objectives. The choice of semantic modelling strategy involves several factors. This discussion will examine the implications of each mode for both BI and Excel users.

You’ve built a Power BI report, and you have two distinct audiences. Each group expects to see different default slicer/filter selections when they open the report. 

With the new TMDL View introduced in Power BI, creating reusable and powerful time intelligence logic is easier than ever.

In this blog, I'll walk you through how to create a Calculation Group with just one click using the TMDL syntax – no need to go through Tabular Editor or external tools anymore.

What is a Calculation Group?

A Calculation Group allows you to create reusable logic for commonly used calculations like:

• Year-to-Date (YTD)
• Quarter-to-Date (QTD)
• Month-to-Date (MTD)
• Current Value (no filter applied)

These can be dynamically applied to any measure, drastically reducing duplication and making your model more maintainable.

One-Click Script to Create Time Intelligence Calculation Group

Simply paste the following TMDL script (Copy/ download from here for correct indentation) into the TMDL View.

This script will instantly add a calculation group named Time Intelligence with commonly used items like YTD, QTD, MTD, and Current.

Want to See It In Action?

I've created a detailed step-by-step video walking you through the entire process, including how to use the calculation group in your reports.

📺 [Watch the full video here]

I Hope you find this helpful !!
Regards
Anmol Malviya

Proud to be a Microsoft Fabric community super user

Let's Connect on LinkedIn

Subscribe to my YouTube channel for Microsoft Fabric and Power BI updates.

In today’s blog, we’ll explore a powerful and time-saving feature in Power BI Desktop: creating multiple measures at once using the TMDL view.

If you work with large datasets or enterprise-level reports, then this trick will definitely boost your productivity.

Why Use TMDL to Create Measures?

Creating measures in Power BI manually one by one can be time-consuming, especially in large datasets or complex models. For example, if you’re building a report that requires 10+ similar measures, switching to the DAX editor for each one can feel repetitive and slow.

Problem with Traditional Method:

• Click on New Measure
• Wait for the model to load (especially slow in large datasets)
• Write the DAX
• Repeat this process multiple times

Solution: Use TMDL (Tabular Model Definition Language) View to create multiple measures in one go!

What is TMDL View?

TMDL is a new feature in Power BI Desktop that lets you edit model metadata (like measures, calculated columns, relationships, etc.) using a simple code editor. It’s like having access to the back-end definition of your model, making it much easier to bulk create or edit logic.

Steps to Create Multiple Measures Using TMDL

Open TMDL View in Power BI Desktop

• Go to the Model view
• Click on the TMDL icon from the ribbon

Locate Your Measure Table

• If you don't have one, create a dedicated Measure Table
• You can also organize measures using folders

Create One Measure as a Template

measure Demo_Measure1 = 1

Add Multiple Measures

• Press Enter to go to the next line
• Use the same structure to add more:

measure Demo_Measure2 = 2

measure Demo_Measure3 = 3

measure Total_Sales = CALCULATE(SUM(Sales[Amount]))

⚠️ Note:

Spaces in measure names are not yet supported in TMDL, so use underscores (_) instead.

Click on the “Apply” Button

• Found on the top-left corner of the TMDL editor
• All your measures will now be created at once in the model

Pro Tip

Let’s say you need to calculate sales by categories (e.g., Electronics, Clothing, Furniture). Just create the logic for one:

measure Sales_Electronics = CALCULATE(SUM(Sales[Amount]), FILTER(Sales, Sales[Category] = "Electronics"))

Then copy-paste and change the category name accordingly. Apply the changes, and you’re done!

Final Thoughts

This method can save a lot of time, especially in enterprise-scale projects or when building demo reports with repeated logic. It’s a great example of how Power BI continues to evolve and empower developers with flexible and efficient tools.

Regards
Anmol Malviya
Sr. Data Analyst | Addend Analytics

Proud to be a Microsoft Fabric community super user

Let's Connect on LinkedIn

Subscribe to my YouTube channel for Microsoft Fabric and Power BI updates.

In today's blog, we're going to explore a powerful tip: how to organize your measures efficiently by bulk moving them into folders or subfolders using the TMDL view in Power BI Desktop.

Why Organize Measures into Folders?

When working on large-scale Power BI reports, you may end up creating 50 to 100+ measures. Managing them in a single list becomes difficult and messy. Organizing these into logical folders or subfolders based on their purpose (e.g., Sales, Revenue, Time Intelligence, etc.) makes your model cleaner and improves maintainability.

Method 1: Using the Table View (Manual)

This is the traditional method:

• Go to the Data view or Model view.
• Click on an individual measure.
• In the Properties pane, locate the Display Folder option.
• Type a folder name (e.g., Demo) and press Enter.
• All selected measures will be grouped under that folder.

📝 Tip: You can also multi-select measures in the Model view and set the Display Folder property in one go.

Method 2: Using the TMDL View (Advanced & Efficient)

For bulk operations and better control, TMDL (Tabular Model Definition Language) view offers a smarter approach.

🔧 Step-by-Step:

1. Go to the TMDL view in Power BI Desktop.
2. Select all the desired measures using Ctrl + Click.
3. Drag and drop them into the TMDL script editor — a code script will auto-generate.
4. Below the format string section of each measure, insert the line: display folder = "Demo_TMDL"
   
5. Once all measures have this line added, click Apply from the top-left corner.

Result:

All your selected measures are now organized into a folder named Demo_TMDL, visible in the Data/Model view.

Bonus: You Can Organize Columns Too!

This functionality isn't limited to measures. You can also create folders for columns using the same method:

1. Go to the TMDL view.
2. Locate the column definitions.
3. Add the line: display folder = "ColumnFolder"
4. Click Apply, and the columns will be grouped into the folder.

Final Thoughts

Organizing your Power BI model is a best practice that boosts readability, reduces errors, and improves collaboration — especially in large-scale projects. The TMDL view gives you the power to manage this efficiently.

Regards

Anmol Malviya

Proud to be a Microsoft Fabric community super user

Let's Connect on LinkedIn

Subscribe to my YouTube channel for Microsoft Fabric and Power BI updates.

In today’s blog, we’ll discuss a highly recommended best practice in Power BI: creating a dedicated Measure Table. This becomes especially important as your report complexity grows and the number of measures increases.

❓ Why Create a Measure Table?

When working on real-world projects, it's common to create multiple measures across various tables. For example:

• A few measures might be in the Customer table
• Others in Sales, Exchange Rate, or other tables

This scattered placement leads to confusion – both for you and your teammates. If someone else opens your report later, understanding where each measure lives and what it does becomes unnecessarily difficult.

👉 Solution? Centralize all your measures in a dedicated measure table. It’s cleaner, easier to manage, and a Power BI best practice.

🛠️ Steps to Create a Measure Table

🔹 Step 1: Create an Empty Table
Go to the Home tab in Power BI Desktop.
Click on Enter Data.
In the dialog box:Click Load.
Power BI will now create a new table with one default column. Don’t worry — we’ll remove that shortly.

🔹 Step 2: Move Existing Measures into the New Table
Let’s say you already have a few measures like Demo 1, Demo 2, Demo 3, etc., located across different tables.

Option 1: Manual Move via Table View
Go to each measure.
In the Measure Tools ribbon, update the Home Table to Measure Table.
Repeat for each measure.

Option 2: Move in Bulk via Model View (Recommended)
Switch to Model View in Power BI.
Select all your measures using Ctrl + Click.
In the Properties pane, find Home Table and set it to Measure Table.
✅ This moves all selected measures at once – fast and efficient!

🧹 Step 3: Clean UpOnce all measures are moved:

Delete the default column (e.g., Column1) from the new Measure Table.
Power BI will now treat this table as a pure measure container, and it will appear at the top of your Fields pane. A neat, clean workspace!

Checkout Step by Step Tutorial for the same: https://youtu.be/LkOPFF4N9RY?feature=shared

🎯 What’s Next?
In the next blog, we’ll cover how to organize your measures into folders inside the Measure Table – perfect when you have 50+ measures across categories like Sales, Profit, Discounts, Time Intelligence, etc.

📢 Final Thoughts
Creating a measure table:

Simplifies navigation in large reports
Improves collaboration with other developers
Enhances performance by reducing confusion and dependency

Regards

Anmol Malviya

Proud to be a Microsoft Fabric community super user

Let's Connect on LinkedIn

Subscribe to my YouTube channel for Microsoft Fabric and Power BI updates.

Power BI continues to evolve, offering powerful tools that enhance the data modeling and visualization experience. One of the latest additions to Power BI Desktop is the TMDL View (Tabular Model Definition Language), a feature currently in preview. This game-changing tool allows developers to script, modify, and apply changes to semantic models directly through code. In this blog, we'll dive deep into the functionalities of TMDL View, its benefits, and how you can leverage it to supercharge your Power BI projects.

What is TMDL?

TMDL offers a folder-based structure for managing your Power BI models, replacing the monolithic JSON file used by Tabular Model Scripting Language (TMSL). Instead of working with one large file, TMDL organizes your model into individual files for each table, perspective, role, and culture. This modular approach enhances clarity and simplifies collaboration, particularly for teams working on complex projects.

Key Benefits of TMDL:

• Improved Collaboration: Multiple developers can work on different parts of the model simultaneously without stepping on each other's toes.
• Enhanced Source Control: Easier to track changes, manage versions, and resolve merge conflicts using tools like Git.
• Simplified Model Management: Quickly locate and edit specific components of your model without sifting through a massive JSON file.

Enabling TMDL in Power BI

To get started with TMDL, you’ll need to enable it in the Preview features of Power BI Desktop:

• Open Power BI Desktop
• Navigate to File > Options and settings > Options
• Under Preview features, check the box next to "TMDL VIEW"

Once the preview feature is enabled, the TMDL view tab will appear on the left side of the Power BI Desktop window:

Exploring Semantic Model Metadata

Even if you're not looking to modify your semantic model, TMDL View is a powerful tool for exploring and understanding model metadata. You can explore any particular measure, column, table or complete Semantic Model. You can either drag and drop the field to the space or simply right click on it and select script tab

By clicking on this you wil be able to see the complete summary of the field as below

Boosting Development Efficiency

TMDL View’s code editor isn’t just for scripting—it’s a comprehensive development environment. Key features include:

• Semantic Highlighting: Easily distinguish between different elements in your code.
• Expand/Collapse: Navigate complex scripts with ease.
• Error Diagnostics: Quickly identify and resolve issues.
• Autocomplete: Speed up scripting with intelligent code suggestions.

For example, if you need to remove prefixes like "dim_" or "fact_" from all your tables, you can script the full model, search for these prefixes using regular expressions, and replace them in bulk.

Applying and Managing Changes

Once your scripts are ready, simply click the Apply button to execute the changes. Successful changes trigger a confirmation notification, while errors prompt a detailed diagnostic message, guiding you through troubleshooting steps.
It’s important to note that TMDL View only modifies semantic model metadata—it doesn’t refresh data or impact report visuals unless those changes directly affect them. For example, renaming a field might break existing visuals that rely on that field.

Use Cases:

TMDL view isn't just about scripting; it's about transforming how you manage and interact with your semantic models. Here are some practical use cases:
1. Bulk Move Measures into a Folder
Organize your measures effortlessly by scripting them into specific folders, enhancing model clarity and navigation.

2. Update M-Code Without Query Editor
Modify your Power Query M-code directly through TMDL scripts, bypassing the query editor for quicker updates.

3. Change Data Types
Easily adjust the data types of your columns using simple TMDL commands, ensuring consistency across your model.

4. Update Summarization at Once
Apply summarization changes to multiple columns simultaneously, saving time and reducing manual errors.

5. Find and Replace
Use the search-and-replace functionality to quickly update naming conventions or correct errors across your model.

6. Switch Between Import and Direct Query
Toggle your data connection modes from Import to DirectQuery or vice versa using TMDL scripts.

7. Import and Collaborate Using TMDL Scripts
Share your TMDL scripts with colleagues via email or platforms like SharePoint, promoting collaborative development.

8. Create Calendar Tables and Calculation Groups
Generate calendar tables and calculation groups directly in TMDL, streamlining time intelligence functions.

9. Utilize Multiple Cursors
Speed up your coding process with multiple cursors, allowing simultaneous edits in different parts of your script.

In upcoming blogs we will share detail about each use case in detail.

Conclusion

TMDL View in Power BI Desktop is a powerful addition that opens new doors for developers and analysts alike. Whether you're looking to enhance efficiency, improve model transparency, or collaborate seamlessly with your team, TMDL View offers the tools you need.

Stay ahead of the curve by enabling this feature today and exploring its vast potential. And don’t forget—we’d love to hear your thoughts and experiences! Share your feedback through the Power BI Community and help shape the future of Power BI.

Ready to dive in? Enable TMDL View in Power BI Desktop and start scripting your way to more efficient data models!

Proud to be a Microsoft Fabric community super user

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Subscribe to my YouTube channel for Microsoft Fabric and Power BI updates.

Creating a robust, reusable Calendar Table is one of the most essential steps in any data modeling process. And now with the introduction of TMDL (Tabular Model Definition Language) in Power BI, this process becomes not just easier but faster than ever—literally in one click.

In this blog, I’ll show you how you can use the TMDL View in Power BI to instantly create a rich calendar table with fiscal year handling, week numbers, month names, and more. You can also check out the step-by-step walkthrough video I’ve created for better visual understanding 📹.

🚀 What is TMDL View in Power BI?
TMDL (Tabular Model Definition Language) is a new declarative way to define tabular models in Power BI using code—making your model components (tables, columns, measures, partitions) more manageable, auditable, and reusable.

With TMDL support enabled, you can now:

• View and edit model metadata in human-readable format
• Create model objects directly using code (like calculated tables, measures, etc.)
• Track and version model changes easily using source control

🧠 Why Use a Calendar Table?
Having a dedicated Calendar Table enables:

• Proper time intelligence (e.g., YTD, MTD, QTD calculations)
• Consistent filtering and grouping across visuals
• Fiscal year handling
• Easier customizations for weeks, months, quarters

⚙️ How to Create Calendar Table using TMDL View?
Here’s a sample TMDL definition for a Calendar Table you can plug into the TMDL view.

🧾 TMDL Code: Download/Copy with correct Indentation from here: (Click)

🔧 Steps to Implement:

1. Enable TMDL View in Power BI Desktop (Preview feature)
2. Navigate to TMDL View in Power BI Desktop and Create a New Script.
3. Paste the code (Copy with correct indentation from here) into the TMDL Script Interface (Refer below screenshot)
   
4. Click on Apply button on top left.
   
5. Calendar table will get created, click on the refresh now button.
   
6. Explore the calendar table from the Data view
   
7. Note: If you want to change the date range or FY Start month then you can change it in the variables created in line 72,73 & 74. (Screenshot attached)
   

🎥 Step-by-Step Video Guide
I've also created a detailed video tutorial showing each step from enabling TMDL to using the Calendar table in your reports.

👉 Watch now on my YouTube channel [ANMOLPOWERBICORNER]
🔗 Video Link: https://youtu.be/ogEcYqf1yJI 

📌 Final Thoughts
TMDL is a game-changer for Power BI developers. With just one snippet of code, you now have a full-featured, reusable Calendar Table ready to go! This will help you:

• Save time ⏳
• Maintain consistency across reports 📊
• Simplify versioning and collaboration using Git ✅

📍 Follow my blog series for more such Power BI TMDL tips and tricks!

Proud to be a Microsoft Fabric community super user

Let's Connect on LinkedIn

Subscribe to my YouTube channel for Microsoft Fabric and Power BI updates.

Have you ever added multiple visuals on top of each other in Power BI and noticed that they don't always behave the way you'd like? Especially when using shapes as backgrounds with cards or KPIs placed on top — clicking the shape often hides the visuals above it.

In this blog, we’ll learn how to manage and maintain the correct layering of visuals using the Selection Pane in Power BI Desktop.

We’re officially into the second week of the Fabric Community DataViz Contest for May 2025 - and the energy is flying high! Whether you're still deciding how to approach your visual, or already in DAX formulas, this post is for you. And if you’ve opened the official dataset we provided, you’ll know it’s absolutely packed with columns waiting to be charted, sliced, and explored in Power BI. So today, we’re going to do a proper walkthrough of the dataset, column by column.

Have you ever wanted to extract raw data from your Power BI semantic models directly into Python?

You're not alone—many developers and data engineers working with Microsoft Fabric and Power BI run into fragmented documentation and scattered solutions. That’s exactly why I wrote this blog.

In this step-by-step guide, you'll learn how to:

• Connect to a Power BI semantic model using adodbapi

• Authenticate securely with Microsoft

• Extract full tables into your Python environment

Whether you're automating workflows, validating data, or building external dashboards—this blog brings everything into one place.

In this blog, we'll walk through a simple yet powerful technique — displaying multiple slicer selections in a card or text box in Power BI. This can enhance user experience by showing selected filters right on the canvas!

Make Smarter Marketing Moves with a Unified Power BI Dashboard

Optimize Campaigns & ROI with an Omnichannel Power BI Dashboard

Customers engage with businesses across a multitude of touchpoints — social media, email campaigns, paid ads, organic search, and more. With such a fragmented marketing ecosystem, understanding which channels truly drive high-quality leads, align with sales goals, and deliver the best return on investment can feel overwhelming.

Many organizations find themselves relying on siloed tools and platforms, each offering only a piece of the customer puzzle. This disjointed view makes it difficult to track performance, calculate ROI or ROAS accurately, and coordinate efforts between sales and marketing teams. The result? Missed opportunities, inefficient budget allocation, and a reactive approach to strategy.

But what if all your data could converge into a single, interactive dashboard, offering a clear, unified view of your customer journey and campaign effectiveness? That’s exactly what the omnichannel dashboard by Power BI delivers.

Designed to be both powerful and user-friendly, this dashboard empowers marketing and sales teams to make data-driven decisions with confidence. From real-time performance tracking to cross-channel attribution, it provides the insights needed to optimize strategies, maximize ROI, and work in sync — all from one centralized hub. It untangles complex data and transforms your marketing and sales strategy from reactive to proactive.

What is an Omnichannel Dashboard?

An omnichannel dashboard is a centralized reporting system that brings together data from web, social media, email campaigns, CRM, sales platforms, paid ads, and more, giving you a 360-degree view of your customer journey and campaign performance. It helps businesses like yours identify:

• The most effective channels
• Customer drop-off points in the funnel
• Revenue-driving tactics
• Campaign ROI in real time

Key Components of an Omnichannel Dashboard

• Overall Insights
  Get a bird’s-eye view of leads, conversions, revenue, and engagement metrics across all platforms.

• Leads Analytics
  Understand where your leads are coming from, which channels convert best, and where they drop off.

• Sales & Opportunity
  Monitor your pipeline — from first contact to deal closure.

• Paid Media Analytics
  Deep dive into ad performance on Google Ads, Facebook, LinkedIn, and more.

• Web Analytics
  Analyze user behavior on your site, bounce rates, top-performing content, and more.
  
  

Visualizing the Marketing Funnel: A Real-Life Use Case

Imagine this — a lead has just entered the funnel at the MAL (Marketing Accepted Lead) stage, full of potential and promise. As they progress toward becoming an SQL (Sales Qualified Lead), the journey gets tougher, with more scrutiny and higher expectations. This is where your sales team steps in, working diligently to ensure the lead stays engaged and doesn’t fall through the cracks. With timely follow-ups, personalized outreach, and the right nudges, the lead eventually converts and becomes a Closed Customer (C-Cust), completing the funnel journey.

This animated funnel isn't just fun — it tells the story of conversion, making your data relatable and powerful.

How Power BI Supercharges this Journey

Power BI acts as the engine behind this funnel visualization, offering capabilities that simplify and elevate your marketing and sales analytics.

• Data Integration

Whether you're using HubSpot, Salesforce, Google Analytics, or LinkedIn Ads, Power BI connects them all, ensuring your dashboard is always powered by real-time, accurate data.

• Interactive & Engaging Visuals

  With animated funnel charts, custom measures, tooltips, and drill-throughs, Power BI lets you create visuals that don’t just inform — they tell a story.

  • ROI/ROAS Calculation at Your Fingertips

  Track your Return on Investment (ROI) or Return on Ad Spend (ROAS) per channel with calculated measures and custom KPIs.

  • Collaboration Made Easy

  Need to share insights with your team? Power BI allows seamless sharing across departments via Power BI Service or Teams integration.

Best Practices for Building Your Omnichannel Dashboard

Creating an effective omnichannel dashboard in Power BI isn’t just about loading in data — it’s about turning that data into meaningful insights that drive smarter decisions. Here are some key best practices to keep in mind:

• Keep Visuals Clean and Focused on Outcomes
  Avoid clutter and information overload. Choose visuals that communicate performance against your goals, such as lead conversion rates, ROI, or campaign effectiveness. Every chart or graph should have a purpose and guide the viewer toward actionable insights.
  
• Use Drill-throughs for Deeper Exploration
  Surface-level metrics are useful, but the real strength of Power BI lies in its ability to let users explore the "why" behind the numbers. Set up drill-throughs that allow users to click into specific campaigns, segments, or timeframes for more detailed analysis without crowding the main dashboard.
  
• Update Dashboards Regularly
  Your marketing strategy is dynamic, and your dashboard should reflect that. Schedule regular data and review your KPIs periodically to ensure they align with current goals, channels, and campaign types. An outdated dashboard can mislead more than it informs.
  
• Validate Data Logic and Source Mapping
  Clean data is the foundation of trustworthy insights. Make sure your data sources are mapped correctly, definitions are consistent across platforms, and calculated metrics (like ROAS or funnel drop-offs) are logically sound. Inaccuracies here can lead to poor strategic decisions.

Final Thoughts

An omnichannel dashboard built in Power BI isn't just another report — it's a strategic asset. It empowers your team to:

• Spot what’s working — and what’s not

• Boost ROI and conversion rates

• Align marketing and sales like never before.