Build a connected planning sheet
Organizations often maintain planning, analytics, and operational data across multiple systems. This fragmentation leads to duplicated data, disconnected workflows, and slow decision-making.
Plan offers a unified suite of capabilities - Planning, Intelligence, and PowerTable - on Microsoft Fabric. Together, they provide a single solution for organizations to build plans, analytics, and data applications directly on top of existing semantic models in Microsoft Fabric.It empowers business users to streamline their planning, forecasting, and reporting workflows; improve decision-making; instantly create apps based on semantic models; and maximize the value of their Fabric investments.
This platform is designed for business users and features a no-code, self-service architecture.
Plan architecture overview
Plan provides three primary workloads that enable organizations to build integrated planning and analytics solutions.
Planning Sheet
Create budgeting, forecasting, and planning applications
Intelligence
Build analytics, dashboards, and reports
PowerTable
Manage master, reference, and operational data.
Together, these workloads allow organizations to combine planning, reporting, and data management into a unified experience.
Plan applications run natively within Microsoft Fabric and leverage the existing semantic model as the foundation for analytics and planning workflow.
This tutorial shows how to create your first Plan(preview) in Microsoft Fabric by generating it from an existing Power BI semantic model.
In this tutorial, you'll learn how to:
Create and configure a planning sheet.
Perform planning and analysis using semantic model data.
Manage master and reference data using PowerTable.
Build analytics experiences with Lumel Intelligence.
Use reference data from PowerTable to support connected planning.
Write back actuals, plans, and forecast values to the Fabric SQL database.
By the end of this tutorial, you'll understand how Lumel enables a unified approach to planning, analytics, and data management within Microsoft Fabric.
The example scenario for this tutorial is a fictional company called Seahills Retail. Seahills is a retail Beverage seller that keeps data on revenue. In the tutorial, you generate discounts, net revenue, and do a forecast on the net revenue for considering various scenarios while bridging data from the power table, and answer questions like: "What is the top product by revenue across all stores?"
Prerequisites
Before starting this tutorial, ensure you have:
Access to Microsoft Fabric.
A semantic model containing business data.
Permissions to create Plan items.
Basic familiarity with Power BI or Fabric semantic models.
Log on to Microsoft Fabric by typing in the URL, https://app.fabric.microsoft.com/ in the address bar. You can also type in https://app.powerbi.com. Kindly note that this link may vary in your Fabric environment.
Before setting up Plan, you need to create your individual DMT connections for connecting with a Fabric SQL database and Power BI Semantic Model.
You also need to create a Fabric SQL database in your workspace. This database stores your Plan report’s metadata.
Set up the Environment
1. Create a Database connection
Go to Settings > Manage connections and gateways.
Select New.
Select Cloud.
Enter a Database Connection name.
In Connection type, select SQL database in fabric.
Set the Authentication method to OAuth 2.0.
Select Edit credentials, and then sign in with your Microsoft account.
Select Create to create the connection.
You can share the created connection and manage the user permissions.
2. Create a connection for the Semantic Model
Go to Settings > Manage connections and gateways.
Select New.
Select Cloud.
Enter a Connection name.
In Connection type, select Power BI Semantic Model.
Set the Authentication method to OAuth 2.0.
Select Edit credentials and then sign in with your Microsoft account.
Click Create to create the connection.
This connection will be used to connect to your semantic models when you create a plan.
3. Create a SQL connection within the workspace
Go to the required Workspace
Add New item and select SQL database.
Give a name to your database and create it.
4. Create Planning Sheet
Go to your Workspace
Create a New Folder
Add New Item > Plan(Preview)
Give a name to your planning sheet and create it
Connect to an existing connection created using the above steps.
Select and Add the database to store your items.
Get your data from the Semantic model or Excel/CSV then create a planning sheet or vice versa.
Here we will show case Creating a Planning sheet and connecting it to a semantic model.
Click Add and Connect to your semantic model connection.
Choose and Add the required semantic model.
Add semantic model data into your fields, and your first planning sheet is created.
Insert a data input measure
We'll insert a data input measure to capture the discount rates applied across regions and product categories.
Select Insert a new empty series from the Number section of the Insert Column menu to create a new data input measure.
Enable the Column Grand Total to enter the discount rate and allocate it across regions and products.
Enter the total discount rate to be distributed across regions and products in the grand total cell. Select the cell and click the allocation icon. Select Distribute by weights of 2025 Gross Sales. The regions and products with higher sales will receive higher discounts and vice versa.
Allocations can be changed at any time during the planning process.
Insert a formula measure
From the Insert Column menu, select Formula. Enter a formula that calculates Net Revenue using the discount rate.
Create a forecast
Click Forecast from the Model ribbon to create a forecast for Q1 2026. Select the Forecast Period - Jan to Mar 2026.
The forecast column is generated for closed periods as well, such as 2025. You can populate the forecast measure using an existing measure in the report or by using a formula. Select Measure as the Closed Period option, and enter the formula in the Formula box.
To populate a closed forecast from an existing measure, select Measure as the Closed Period option, and then choose the measure from the Linked Measure menu.
3. Set Open Period to Measure or Formula to populate the forecast using an existing measure or a formula. Select Data Input to allow users to manually enter forecast values. Click Create.
Initialize the forecast values using an existing measure in the report. Select the measure from the Copy Source menu. Select Blank to manually enter all the values.
5. You can use existing measure values to initialize forecasts in three ways: for a range of periods, for a specific period (month, quarter, or year), or as the average value over a period range. Click Save.
The forecast is generated with read-only values for closed periods and initialized using existing measure values for open periods.
Scenarios
Scenarios allow planners to evaluate different business outcomes by modeling alternative assumptions on the same dataset. Instead of relying on a single forecast, scenarios help teams compare multiple possibilities, such as best-case, worst-case, or expected outcomes, and understand how changes in key drivers affect business performance.
Planning sheets scenarios enable users to create independent versions of planning data without modifying the baseline values. Each scenario stores a separate set of inputs and calculations, allowing users to simulate different strategies and compare their impact across measures, dimensions, and time periods.
Consider that Seahill Retail wants to change its discount percentage during the Holiday season and know how it affects its net revenue. Scenarios help you to do it.
Create a Scenario
Go to Model > Scenario
Enter a scenario name and include the series in the scenario
Create the scenario.
Simulate the cell values by sliding the slider and increasing or decreasing the discount percentage.
Net revenue changes according to the simulation.
Save the scenario after updating inputs and reviewing results.
Scenario Ribbon features
Create - Create a new scenario by copying values from an existing scenario or the base plan. This allows planners to test alternative assumptions while preserving the original data.
Compare - Compare multiple scenarios side-by-side to evaluate differences in measures, dimensions, or time periods. This helps identify the impact of different planning assumptions.
Settings -Configure scenario properties such as the scenario name, description, and other configuration options.
Simulation - Run interactive simulations by adjusting planning drivers or inputs. This enables quick evaluation of how changes affect overall results.
Show variance - Display the variance between the selected scenario and the base scenario to highlight differences in values.
Slider settings - Configure sliders used in simulations, including the range and behavior of adjustable inputs.
Reset - Revert changes made in the current scenario back to the original values copied from the base scenario.
Copy to base - Apply the values from the current scenario to the base scenario when the simulated results need to be adopted as the new baseline.
Bulk Edit - Update multiple cells or values simultaneously within the scenario to accelerate planning adjustments.
Pivot - Change the layout of rows and columns in the Planning Sheet to analyze scenario results from different perspectives.
Writeback - Save scenario inputs to the configured data destination or planning storage.
Add destination - Configure a new writeback destination where planning data or scenario results can be stored.
Writeback plans, scenarios, and forecasts
Export calculations, data inputs, forecasts, scenarios, and simulations, along with native measures, to a SQL database in Fabric.
Set the writeback table structure from the WB Type menu in the Writeback ribbon. Select Long to store measures as key-value pairs.
2. Enter the database connection, name, schema, and table name to configure the writeback destination. Click Add.
Choose whether to write back only the report or include any associated scenarios. Select Writeback All from the Writeback dropdown. Select the scenarios to writeback. Click Writeback.
Click Logs to view the writeback run history.
Connected Planning
Using the steps outlined above, you would have created a plan, forecast, and a few scenarios before writing back all data to your preferred database.
In a connected planning scenario, you start with actual revenue data and then add context from external sources like Excel files or reference tables from other data platforms. The additional context can include information such as store footfall, demand change forecasts, promotional campaign projections, and so on. You can use them for calculations within the Planning sheet or perform further downstream processes.
This approach involves two steps:
Use PowerTable to access reference data from an existing database, such as an external forecast projection. PowerTable connects directly to the database containing the reference data.
Then, using Infobridge, connect to PowerTable, query data, and perform the necessary transformations to bring it into the Planning sheet.
Note
Infobridge is a no-code, data integration, preparation, and transformation engine included in Plan. It lets you connect to multiple data sources (Excel. CSV, Parquet, other planning sheets, etc.), transform the data, and consolidate them into a unified dataset for planning and reporting.
Create a PowerTable Sheet
In your Plan, click on the + and then select PowerTable to add a new PowerTable sheet.
Note
The forecasts, scenarios, and a few formula measures are hidden in the Planning sheet below for easy demonstration. You do not need to duplicate the planning sheet or hide the measures in the actual use case.
Enter a name for the sheet and click Create.
Click on Create a New App to create an app.
When creating a new app, you need to select a DMT connection to connect to your Fabric SQL database. Select a connection and click Connect.
Select your Fabric SQL database. The metadata for your app is stored here. Click Add.
Select Existing Table to connect to an existing table (Proj) in the Fabric SQL database. Select the Schema and the Table Name containing the reference data. Click Next.
PowerTable detects column properties automatically. You can edit them if necessary. After verifying the details, click Finish.
You have now successfully connected to the required reference database using PowerTable. You can see the Projected Revenue column. Click Save to save the report if it is not saved.
Create a bridge to connect to PowerTable
Using InfoBridge, you can connect to this PowerTable sheet and bring in the additional measure, Projected Revenue, to the Planning sheet.
Expand the Queries section in the Data pane.
Select Add, and then choose the external data source to connect to (Excel, CSV, Planning sheet, PowerTable, etc.). Here, you can choose PowerTable Sheet.
Alternatively, you can also select Create From Scratch to create a bridge from scratch.
Select the PowerTable sheet you created and click on Preview to preview the data.
In the preview screen, you can preview the data, add filters if necessary, and click Add.
The Infobridge screen opens with PowerTable data added as a query. Here, you can transform your data to match the planning sheet data.
Use Column Data type option to convert the data type of any columns (Year, Quarter, etc.) and Pivot Table to arrange your rows and columns as required. Click Apply to apply the transformation.
The data is now transformed.
Go to the Planning sheet to view the query on the Queries pane.
You can add values from here to the planning sheet's Values field. You have successfully connected a projected revenue measure from the reference database to your planning sheet.
This is one of the examples for connected planning
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