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Microsoft Cloth: Producing Experiences with Copilot

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Microsoft Cloth: Producing Experiences with Copilot

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Microsoft Fabric Generating Reports with Copilot on Fabric

In Nov 2023, Microsoft introduced Microsoft Cloth’s basic availability and Public Preview of Copilot in Microsoft Cloth. In a earlier put up, I defined what Copilot means to Energy BI builders, which is legitimate for different Cloth builders akin to information engineers and information scientists as Copilot for Cloth helps with these experiences as properly. However the principle focus of this weblog put up is to debate the necessities, how you can allow Copilot, and how you can use it from a Energy BI improvement viewpoint. So, this weblog won’t focus on different elements of Copilot in Microsoft Cloth. With that, let’s start.

Proper off the bat, Copilot is barely obtainable on Energy BI Premium capacities or their equal Cloth capacities. So, NO it’s NOT obtainable on Energy BI Professional or Premium Per Person or Energy BI Embedded Analytics. So the Energy BI objects you need to use Copilot on have to be in a Workspace assigned to a Energy BI Premium P1 or Microsoft Cloth F64 capacities or larger.

You additionally must have a Contributor position on the premium workspace.

To make use of Copilot, your Microsoft Cloth Administrator should allow it from the Cloth Admin Portal. This setting shouldn’t be obtainable in all areas but, however Microsoft is step by step rolling it out to extra areas.

Enabling Copilot on Cloth Admin Portal

As talked about earlier than, your Cloth Administrator should allow Copilot options throughout the Admin Portal. Comply with these steps to allow Copilot in your tenant after logging into Microsoft Cloth:

  1. Click on Settings (the gear icon on the highest proper of the web page)
  2. Click on Admin portal
  3. Make sure that the Tenant setting tab is chosen
  4. Scroll all the best way right down to the Copilot and Azure OpenAI Service (preview)​ part

Notice

You may also use the search field and seek for OpenAI to seek out the Copilot and Azure OpenAI Service (preview)​ part.

  1. Allow the Customers can use a preview of Copilot and different options powered by Azure OpenAI
  2. Click on the Apply button
  3. Allow the ​​​Knowledge despatched to Azure OpenAI could be processed outdoors your tenant’s geographic area, compliance boundary, or nationwide cloud occasion
  4. Click on the Apply button once more

That’s it. You enabled the Copilot capabilities in your tenant.

The next picture exhibits the previous steps:

Enabling Copilot for Power BI in Fabric Service Admin Portal
Enabling Copilot in Cloth Admin Portal

Listed here are some vital notes to concentrate to:

Notes

  1. Whereas it is a Preview function, I’d strongly suggest studying via the Phrases of use earlier than enabling it in your tenant, particularly if in your Manufacturing tenant.
  2. These configurations apply tenant-wide. We at present can’t limit it to particular safety teams.
  3. Microsoft has achieved a fantastic job in highlighting a notice when enabling the Customers can use a preview of Copilot and different options powered by Azure OpenAI setting that claims:

If Azure OpenAI shouldn’t be obtainable in your area, your information might have to be processed outdoors your tenant’s geographic area, compliance boundary, or nationwide cloud occasion. To permit information to be processed in a area the place Azure OpenAI is offered, activate the associated setting, “Knowledge despatched to Azure OpenAI could be processed outdoors your tenant’s geographic area, compliance boundary, or nationwide cloud occasion”.

  1. Take note of one other notice highlighted underneath the ​​​Knowledge despatched to Azure OpenAI could be processed outdoors your tenant’s geographic area, compliance boundary, or nationwide cloud occasion part saying:
    Even when this setting is on, additionally, you will must activate the associated setting “Customers can use a preview of Copilot and different options powered by Azure OpenAI” for these options to work.​
  2. I encourage you to learn Microsoft’s documentation round Accountable use for Copilot in Energy BI.

With that, now allow us to use Copilot on Cloth service and see the way it generates experiences.

Producing experiences with Copilot is tremendous simple. Comply with these steps to generate your first report with Copilot:

  1. Navigate to the specified premium workspace
  2. Hover over the specified semantic mannequin and click on the Extra choices ellipsis button
  3. Click on Create Report
Creating a new report in Fabric Service for using Power BI Copilot
Creating a brand new report in Cloth Service
  1. On the brand new report, click on the Copilot button
  2. Click on the Create a web page that exhibits… button
  3. Sort in to clarify the way you want the Copilot to generate the report
  4. Submit your request by urgent Enter in your keyboard or clicking the submit button
Generating Power BI report with Copilot in Microsoft Fabric
Producing Energy BI report with Copilot

There you go! You may have it!

Power BI report generated by Copilot in Fabric Service
Energy BI report generated by Copilot

It seems to be fairly cool, doesn’t it? However wait, there’s something mistaken with the report. Have you ever observed the road chart within the backside proper of the report exhibits a flat line for Web Gross sales and Web Revenue by Product Class? It can’t be right. This takes us to the following part of this weblog put up, the place we focus on some ideas and methods.

As Copilot seems to be on the construction of the semantic mannequin to generate experiences for us, it’s essential to make the semantic mannequin as optimised as attainable. For instance, within the earlier picture, we are able to shortly spot a problem mirrored within the Web Gross sales and Web Revenue by Product Class line chart on the underside proper of the report web page the place the chart exhibits a relentless line for all product classes. This means a possible lacking relationship between the Product Class and the Web Gross sales tables contributing to the connection. Let’s look into this.

The next picture exhibits the information mannequin the place I put the required tabled as a brand new structure:

Power BI Semantic Model Data Modelling Issues
Lacking relationship in Energy BI semantic mannequin

As you possibly can see, the lacking relationship is certainly between the Product Subcategory and Product tables, which led to incorrect ends in the reporting layer. Creating the connection between the 2 tables fixes that difficulty as proven within the following photographs:

Creating new relationship in a semantic model in Fabric Service (Power BI Online)
Created the lacking relationship
Fixing reporting issues by creating the missing relationship between tables in Power BI data model
Mounted report after creating the lacking relationship within the semantic mannequin

As you see, semantic mannequin points can result in reporting points generated by Copilot. Nicely, let’s face it, that is precisely what we count on to occur even when we manually create the report, isn’t it?

The previous instance leads us to the next ideas and methods to get the very best Copilot expertise:

  • Get the relationships proper: as we noticed within the above instance, lacking or incorrect relationships will result in inaccurate information visualisation.
  • Naming conference: Use extra user-friendly names within the information mannequin. For instance, Complete Gross sales as a measure title can be extra comprehensible than TotalSales. Enjoyable truth: Nobody likes Col1 or Tble1 names for any objects, particularly Copilot.
  • Create specific measures: It’s higher to have specific measures within the information mannequin as an alternative of implicit measures. Only a fast notice for many who have no idea the distinction between specific and implicit measures:
  • Implicit measures: Implicit measures are columns proven with a Sigma icon () within the Knowledge pane in Energy BI. These columns are routinely detected as measures when utilized in a visible on the reporting canvas. In different phrases, we don’t create implicit measures.
  • Specific measures: However, the express measures, are these ones we create throughout the information mannequin utilizing DAX. The express measures additionally seem within the Knowledge pane in Energy BI. The icon for specific measures seems to be like a calculator ().
  • Comply with star schema mannequin design: Create truth and dimension tables following the star schema design. For instance, it’s best to maintain additive, measurable and quantitative information, plus international keys of the dimension tables. In distinction, preserve the descriptive information within the dimension tables.
  • Create hierarchies: Creating hierarchies in dimensions helps Copilot perceive the information grouping higher. That is useful, specifically with figuring out drill-down actions.
  • Take note of information sorts: Defining right information sorts for measures and columns within the information mannequin helps Copilot to generate higher experiences. For instance, utilizing Date information kind as an alternative of Textual content helps Copilot to grasp it’s coping with date values as an alternative of textual content.
  • Use less complicated prompts: In my expertise with the report era functionality of Copilot for Energy BI, it performs finest when utilizing less complicated prompts with minimal circumstances, akin to Create a web page that exhibits Gross sales by Product as an alternative of Create a web page that exhibits Gross sales by Product the place Procust Class is “Equipment” and Calendar Date is 2012. Whereas it nonetheless generates the report, its accuracy decreases by elevating the complexity of our immediate.

The Copilot for Energy BI does a superb job of producing experiences, particularly in its early phases. We will use this function to make experiences, however we must be conscious that there is likely to be issues, particularly if we haven’t made our information fashions higher. We have to verify and repair the experiences.

As all the time, please share your ideas and opinions with us.

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