Analyze emissions data

  • 5 minutes

After the data loads into the lakehouse, you can use the prebuilt Microsoft Power BI dashboard for analyzing the emissions. The prebuilt dashboards allow you to drill down and compare Azure emissions data across subscriptions and resources. You can also visualize trends in Azure emissions data based on the resource changes.

Screenshot of the Overview tab in Microsoft Azure emissions showing emissions data.

By using the Compare emissions tab in the report, you can compare emissions across two subscriptions.

Screenshot of the Compare emissions tab in Microsoft Azure emissions showing emissions data.

Use Copilot to ask questions

If you activated Microsoft Copilot in Fabric, you can use it to analyze the data and generate insights. The following image shows an example of asking Copilot to provide an executive summary.

Screenshot of Copilot with suggestions and a summary.

Build custom visualizations

You can modify the provided emissions Power BI report to add your own branding, custom pages, and any other supported Power BI report customization. If you have Copilot turned on in your Fabric workspace, you can also interact with it to create custom visualizations.

The following example shows a scenario where you ask Copilot to create a page to analyze emissions by subscription and provide insights into the environmental impact of each subscription.

Screenshot of Copilot with insights into the environmental impact of each subscription.

Copilot analyzes the semantic model and then creates the following custom page.

Screenshot of the custom page with analysis by using the semantic model.

Use the SQL analytics endpoint

You can take advantage of the ComputedESGMetrics lakehouse by using the SQL analytics endpoint. By using this approach, you can query the lakehouse data by using your own impromptu queries.

In the lakehouse, you can view two primary tables: azure_emissons and emissions_summary. By using the model layout, you can view the available columns on the two tables.

Diagram of the model layout with the available columns on the two tables.

With knowledge of the data model for the tables, you can create queries to review the Monthly Total Emissions by region and service category.

    SELECT 
        es.AzureRegionDisplayName, 
        es.ServiceCategory, 
        es.DateFormat, 
        SUM(
            es.Scope1CarbonEmission + 
            es.Scope2MarketCarbonEmission + 
            es.Scope3CarbonEmission
        ) AS TotalCarbonEmissions
    FROM 
        [SDS_ESGDE_DYSC3_ComputedESGMetrics_LH].[dbo].[azure_emissions] es
    GROUP BY 
        es.AzureRegionDisplayName, 
        es.ServiceCategory, 
        es.DateFormat
    ORDER BY 
        es.DateFormat DESC, 
        es.AzureRegionDisplayName;

When you run the query on the SQL analytics endpoint, you get a result that's similar to the following image.

Screenshot of carbon optimization on the Emission Reductions page.

You can query the emissions data by using the REST API. For more information, see Access emissions data through APIs.