What fields and calculation to use when trying to create a burndown chart from Azure Dev Ops into Power Bi - azure-devops

I'm currently trying to create a burndown chart using data pulled through Azure DevOps into Power Bi using the Power Bi Connector.
The problem I'm having is that I can't find a field which contains the effort and amount of time a task took. The best I can find is adding a analysis view in Dev Ops and the field 'Remaining Work' however when a task is completed this field blanks.
Has anyone done this before, do they know what fields to use and what DAX(s) expression would be used to generate a burndown chart in PowerBi for Azure Dev ops?
Thanks for your help.

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PowerBI - DevOps

How would I create a powerBI report that shows the real sprint burndowns but connecting to the AzureDevOps environment?
Is there a downloadable .pbix template available?
Regards
That's a nice to have option but yet to be available. There are many workarounds that you would try
Embed the reports from Azure DevOps burn down in Team Site / SharePoint Online portals
Create Power BI reports as per the need. The step by step approach is shown in Link
Thanks
There is no,you need create it your self.
Analytics views dataset design
Connect to Analytics with Power BI Data Connector

How to retrieve Velocity data that's used for Azure Dev-Ops Analytics Velocity Dashboard Widget?

I want to retrieve the backend data that's used to specifically drive the Azure DevOps Analytics Velocity Dashboard Report [Committed and Completed Points for each interaction]. I would like to pull this data either using OData feed or the Visual Studio Team Services (Beta) in order to create custom PowerBI reports
[1] Example of the report I'm trying to pull the data from can be found here:https://learn.microsoft.com/en-us/azure/devops/report/analytics/_img/velocity-ax-catalog.png?view=vsts
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Please see What are Analytics views for details.
When using the Power BI Data Connector, these same default views
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Default Analytics views work well for customers with small datasets.
To learn more, see Default Analytics views.
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