Dataverse on Hat Full of Data

Microsoft Fabric – Using Copy Job with Dataverse

Thu, 27 Nov 2025 15:35:41 +0000

Dataverse is the data store behind parts of Dynamics and lots of Power Platform projects. So Dataverse can contain vital business data that will be needed for reporting. In this post we are going to look at one method which is using copy job with Dataverse to copy across data in Microsoft Fabric.

Scenario
First Copy Job – Dataverse Connector
Copy Job Run
Copy Job using SQL Server connection
Incremental and Merge Running
Trouble Shooting
Alternative Options to using Copy Job with Dataverse
Conclusion

Scenario

For this post we will look at 2 tables, Accounts and Contacts so all the code will be common to any Dataverse environment. I have 5 Account records and 10 Contact records. I also have the environment path org29d4c6d3.crm11.dynamics.com.

In Microsoft Fabric I have a workspace, Finance Reporting, with a Lakehouse, Finance_Lakehouse.

First Copy Job – Dataverse Connector

Copy Job is a great artifact to move data easily into Fabric. Simplest version just copies data, we can then add incremental and merging. More details can be found here https://learn.microsoft.com/en-us/fabric/data-factory/what-is-copy-job

For the first example we will copy from Dataverse using the Dataverse connector. The wizard that walks you through creating a Copy Job has 6 steps. For this first one we will walk through each step.

Create Copy Job

Either using a task flow Get Data’s add item or using Add item in the workspace, select Copy job. Type in a name and click Create.

Choose Data Source

Next step is connecting to Dataverse. For this example we are using the Dataverse connector. Click on the Dataverse option under New sources. When the next screen appears enter in the Environment domain. If it is your first time connecting there you will be given the option to name your connection and select a privacy level. It will guess the authentication and login – this is not the blog to discuss options here.

Once these are done click Next

Choose Data

Choosing the data is very simple, the next screen lists the tables from dataverse using their display names and logical names in brackets. Yes they call them Entities…. No comment. If you expand a table the logical names of fields are listed. There is a search box that will allow you to search for a table using either of the names. If you have selected a table the search will expand to the field names as well. Interestingly for choice columns you only get the code column, not the name column. That is going to be another post!

If you select a table all the columns will be imported. You select the required columns manually by selecting individual columns, its a touch manual and requires searching and scrolling lots in my experience. Next version is better in my opinion – feel free to scroll down!

When you’ve selected your tables and columns click Next.

Choose Data Destination

Data destination is another easy step. Select your lakehouse from the OneLake catalog.

Choose copy job mode

With the dataverse connector you only get one option, Full copy. In the Map to destination you get to choose if that is an append or overwrite.

Map to destination

The next screen shows update method and the tables being imported. Clicking on Edit update method will give you the option of Append or Overwrite. Append is the default but this will just duplicate you data every time you run this copy job. I have changed it to Overwrite. Merge is not available in this version.

You can enter names for your destination tables and click Edit column mappings to tweak column names or remove some mapping. The columns selected will match the columns you selected back in Choose data.

Click Next once you are happy.

Review + save

The final screen will give you an overview of what the copy job is going to do. You can select if you want it to run now, run once or scheduled. I’m choosing to let it run so I’ll just click Save + run

Copy Job Run

When a copy job runs such as after saving in the previous steps you can see the execution happening. Each table is listed and when it succeeds you will see how many rows were read and how many were written. In our example read and written are the same.

Once the run has completed we can go check the Lakehouse and we can see tables. It might need a refresh to show.

Copy Job using SQL Server connection

Although the dataverse connector works, the selection of columns is very manual. You also get no option for incremental updates or using merge. So the next example will use SQL Server connector. In a previous post https://hatfullofdata.blog/using-sql-on-dataverse-for-power-bi/ I show how you can use SQL on Dataverse with some great hints from Scott Sewell.

From that post and with the addition of the modifiedon field here is the SQL for the accounts table. We will use this later.

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Select
	accountid as AccountID,
	name as Account,
	industrycodename as Industry,
 modifiedon,
	statecode,
	statecodename
from
	dbo.account

New Copy Job using SQL Server

Create a copy job as before giving it a name. For the connector select SQL Server. The Server is the environment path as used before, e.g. org29d4c6d3.crm11.dynamics.com. Remember to edit the connection name and privacy level. There is no point adding a Database, it makes no difference. After you press next you need to wait for the database list to load and then select the only database offered.

Choose Data

The next screen for choosing the data starts by showing you an error. Ignore that, it means you can’t use the interface to select your tables and columns but you can add queries. Expand Queries in the bottom left and click on New query. Type in a name, eg Accounts and then in the query box on the right put in your query. You can check it returns the right data by clicking on preview data.

Repeat the above for each of your tables and then click Next.

Incremental and Merge setup

When you choose your lakehouse in the data destination and move onto the copy job mode screen you now get 2 options, Full copy and Incremental copy. The incremental copy will initially copy everything and then in the future will only copy across changes. In order to recognise which records have changed you need a data time column of when it last changed. Hence we have included the modifiedon column.

So incremental is only going to process updated or new rows, but what do you want done with those new rows? Append will add the newly updated rows giving you the complete history of each row. Overwrite you will loose rows that have not been modified. Merge is currently in preview but would allow you to update the row that matches on a unique field, e.g. Account Id.

Click Incremental and then Next. In the Map to destination screen, click on Edit update method and select Merge and then select the unique id column for each table. When you click next you will be prompted to select the incremental date time column for each table. Click next to the final stage.

Save, Review and Schedule

On the final screen not only do you get to save and review but you also get to schedule due to us picking incremental. You can pick repeat by the minute or hourly and pick dates etc. Be aware incremental requires more compute so will consume compute faster than a straight copy but on huge tables the reduced copy will be worth it.

Select your options and Save and Run

Incremental and Merge Running

The first time we run just as before the rows read and written include all the data. If we go and edit one row in the accounts table and re-run the copy job, only one row is read and written for the accounts table and nothing for the contacts table.

Trouble Shooting

In preparation for this post I’ve hit a number of issues.

Although there is a back button in the wizard, going back to the data source and tweaking the queries just breaks the copy job.
You name a column in the SQL with a space, that update will fail with a weird error. No spaces in column names!

Alternative Options to using Copy Job with Dataverse

Link to Microsoft Fabric

Using the Link to Microsoft Fabric in Dataverse sounds like a great option. You will be able to add shortcuts in a Lakehouse to the data and it will all be awesome.

Just after you select the workspace that the data will go to there are 2 short sentences that you should read carefully.

“We will link all tables so that you don’t have to choose. You may incur additional charges.”

I’ll not comment on the “so you don’t have to choose” as I’m not sure I have anything polite to say. That additional storage is in Dataverse which could cost $40 per 1GB per month and with all the tables that could easily become a huge expense, even empty tables take up space. All this so we can have a shortcut in Fabric.

Platform Guardian blog has a great post to walk you through doing thishttps://platformguardian.blog/2023/11/05/creating-the-dataverse-connector-in-fabric/

Conclusion

Copy Job is one of my favourite Fabric artifacts because they are simple to set up. Editing them is foul so I end up re-building them. Its a brilliant low-code solution to copying across data from dataverse and into a lakehouse. Be aware incremental is going to eat capacity so don’t bother with small tables just do a full copy over writing every time.

I don’t see any benefit using the dataverse connector except you don’t have to write SQL. A simple select statement is not complex I’m sure an AI prompt somewhere will help you out.

Power Platform Solution and Power BI – Part 3

Mon, 22 May 2023 22:17:42 +0000

In Part 1 we added Power BI to the Power Platform solution and then in Part 2 we added a dashboard. This is post we will embed the report into a form and filter the report to match the context of the form. For this we will use the Accounts form and filter the expenses report to only show the expenses related to one account.

Series

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Embed the report into a form.

In my Power Platform solution, the Accounts table has one form included. When I edit the form I can see that I previously added a tab for expenses. On that tab there is an empty section, ready to insert the report.

In the left hand side menu, select components and expand Power BI. Drag and drop Power BI report into the blank section. An pane appears asking lots of questions regarding showing various parts. For now leave all of them as default and click Done. The unfiltered report should appear.

Filtering the embedded report.

The report needs to be filtered to only show the expenses of the selected account. With the report selected you will get the properties pane showing on the right hand side. Expand Components and click on Power BI Report. In the pane that appears, same as before find JSON filter string. You need a JSON string to put in the Static value.

The filter we are going to apply is straight forward match the account id on the form with the account id in the report. We need 3 bits of information

Power BI Report table name – Account
Power BI Report column name for the account id – AccountID
Dataverse logical column name for account id – accountid

You must get the case and of course the spelling right. We then insert these into a json string. The whole string must be on one line, no returns and tabs to make it pretty. Below is an image to explain the parts and below that is the code I used.

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{"Filter": "[{\"$schema\":\"basic\",\"target\": {\"table\":\"Account\",\"column\":\"AccountID\"}, \"operator\":\"In\",\"values\":[$a],\"filterType\":1}]", "Alias": {"$a": "accountid"}}

When editing a form in Dataverse, the form is in new record mode so if you have the filter right the report should filter to nothing. When it is working click Done and Save and Publish your form.

Testing the form

Make sure you test your form. Open your app, open an account and look at the expenses and the report. If your report is a direct query report you should be able to add a new record and the report update.

Conclusion

The three posts combined gives us the building blocks to include Power BI in our Power Platform Solutions. I’m hoping more Power BI artefacts such as dataflows also get included in time. There will be future posts, let me know what you want me to do.

Here are the resources I usedAbout Power BI in Power Apps Solutions – Power BI | Microsoft Learn

Power BI Series

Power Platform Solution and Power BI – Part 2

Sat, 20 May 2023 19:08:20 +0000

Intro – Add a Dashboard

In Part 1 we added a Power BI dataset and report to a Power Platform Solution. In Part 2 we will create a dashboard and add it to the model driven app.

Series

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Create the Dashboard

In the solution click on +New and select Dashboard and then Power BI embedded. When the pane on the right hand side loads, enter in a name for your dashboard. Then make sure Power BI report is selected and select your report from the drop down.

Add the Dashboard to the App in the Power Platform Solution

After the dashboard has been added, you can add the dashboard to a model driven app. Edit the app by clicking on the name of it in the Power Platform Solution. Then click on Add Page and the New page dialog appears. On the first page select Dashboard and then click Next. Then on the next page, select your report, probably at the bottom of the list. Finally click Add to add the dashboard to your app.

Note

At the time of publishing there is a small bug that the report doesn’t show correctly in edit mode but if you publish all customisations it fixes it in play mode. Remember this feature

Testing the Report

As with any addition to a development you should test the report works. In my example the report is a direct query. So my test is check the dashboard, then add a new expense record and then return to the dashboard to check the new record is showing.

Conclusion

For some projects this is enough, an embedded dashboard in the model driven app. The next post will be to add an embedded report into a form.

As in Part 1 here are the resources I’ve used

About Power BI in Power Apps Solutions – Power BI | Microsoft Learn

Power BI Series

Power Platform Solution and Power BI – Part 1

Fri, 19 May 2023 08:26:43 +0000

Power BI reports can be an important part of a Power Platform solution. Microsoft has added a new feature to Power Platform Solutions to add a Power BI dataset and report. Then you can add the Power BI report in as a dashboard or as an embedded report in a form and add context filtering. Part 1 will cover adding the Power BI dataset and report to the solution.

Series

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Preparation

For this post I have a Power Platform solution already. I have a Power BI report connected to the environment and published to a workspace.

Add Power BI to Power Platform Solution

First task is to add the Power BI report to the solution. Start by clicking on Add Existing and from Analytics selecting Power BI report. This will bring the underlying dataset in as well. Then click on From Power BI which will show you a workspace drop down*.

From the drop down, we select the right workspace and then the right report. Then we click on Add.

It takes a while for the dataset and report to be added. Behind the scenes a new workspace is created and the report is copied to there. If you don’t have permission to create a workspace you will get errors.

Checking the New Workspace

I recommend that you check the workspace. Check the credentials in the dataset and refresh the dataset and finally make sure the report opens and shows data. Remember to setup a refresh schedule if your report needs it.

Note the message across the top telling you that this is a workspace connected to a solution and the workspace icon is the Power Apps icon.

Finishing the connection part

The report is connected to this environment’s Dataverse. When the solution is exported and imported the report needs to be connected to the new environment’s Dataverse.

In the solution, I clicked on the three dots and selected Edit. Then a pane will appear on the right. Then select Yes from for the existing connection question and click Save.

Conclusion and Resources

Congratulations, you now have a solution that includes a Power BI report.

This is just Part 1. The future parts will cover adding a dashboard and an embedded report. Here are the resources I have used.About Power BI in Power Apps Solutions – Power BI | Microsoft Learn

Power BI Series

Using SQL on Dataverse for Power BI

Wed, 26 Apr 2023 16:55:19 +0000

SQL (Structured Query Language) has been used to get data in and out of databases for decades. Dataverse is a database. So lets use SQL on Dataverse to fetch data into a report. This can simplify our queries and make a direct query report easier to write.

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Microsoft SQL Server Management Studio

There are multiple tools available to write and test your SQL, for this post I am using SQL Server Management Studio (SSMS), which is a free tool from Microsoft. You can download SSMS from

https://learn.microsoft.com/en-us/sql/ssms/download-sql-server-management-studio-ssms

After you have downloaded SSMS, you can start it. Then you need to login to the specific environment. A dialog should pop up to fill in or you can click Connect. The Server type is Database Engine. The server name is in the url path from running a model driven app.

For this post the authentication I am using is Azure Active Directory – Password. So I also supply a User Name and Password. Then you can click Connect.

When connection has completed, the Object Explorer pane will show the hierarchy of items. Expand Databases to find your environment database and then expand that database and Tables to see the complete list of tables. Expand the table to see the list of columns.

Write your first query

This post is not to teach you SQL. There are plenty of sites to do that. Here are some very simple queries to get you started. For our first query, we will write a query to fetch a list of accounts. Click on New Query and a blank page appears. In here we can type a simple query to list all accounts. Click Execute to run the query and see the results.

SQL Code

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Select
	accountid as AccountID,
	name as "Account Name",
	industrycodename as Industry,
	statecode,
	statecodename
from
	dbo.account

Filtering the data

The previous example includes an account that is not active. Contoso Pharmaceuticals has a statecode of 1 and statecodename of Inactive. For this example we are going to filter to only show the active records. The active records have 0 in the statecode column. The WHERE clause applies the filter. The statecode and statecodename columns can be removed.

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Select
	accountid as AccountID,
	name as "Account Name",
	industrycodename as Industry
from
	dbo.account
where
	statecode = 0

Using SQL on Dataverse in Power BI

Now we have an SQL statement we can use it in Power BI. Start POwer BI and then click Transform data to open Power Query. Then we create a parameter by clicking Manage Parameters and then click New and fillin in the details. The current value should be the environment path you used earlier.

Now you have the parameter we can create the query. Start by creating a blank query by clicking New Source and then Blank Query. Then on the Home ribbon click Advanced Editor and paste in this code. I have adapted a pattern created by Scott Sewell.

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let
 Dataverse = CommonDataService.Database(Environment, 
 [CreateNavigationProperties=false]),
 SQL = "Select
	 accountid as AccountID,
	 name as ""Account Name"",
	 industrycodename as Industry
 from
	 dbo.account
 where
	 statecode = 0",
 Source = Value.NativeQuery(
 Dataverse,
 SQL,
 null,
 [EnableFolding=true]
 )
in
 Source

Note 1 – the CreateNavigationProperties and EnableFolding are important flags to help with performance. Scott Sewell explains both topics in these posts.

https://www.linkedin.com/pulse/speedtip-enablefolding-option-dataverse-native-sql-power-sewell/https://www.linkedin.com/pulse/stuck-evaluating-dataverse-source-power-bi-try-speedtip-sewell/

Note 2 – If your SQL includes any ” you will need to double them up inside the string. In this example the ” is needed as the column Account Name has a space in it’s name.

For other queries you just replace the SQL = step with a different SQL statement. You can add further transformations if you need them into Power Query. Remember to rename your query to a clear name.

Permission to Run a Native Database Query

SQL is a powerful language. On some databases, not Dataverse, it can edit or delete the data. So Power Query will check the first time it runs any query. A message in a yellow bar appears stating Permission is required. When you click Edit Permission, a dialog appears showing you the query and you can click the Run button. Then the data will appear.

Loading into Power BI Desktop

Now you have a query that loads data you can load it into Power BI desktop by clicking Close & Apply on the home ribbon. Before it will load the data it will ask you to set the storage mode. For this post I am selecting DirectQuery. This means the data is live and data security is applied using the report viewer’s security. (See publishing to get this 100% right)

It will ask you confirm running the query again, just click Run. Once the data has loaded we add relationships if required, measures and visuals into the report. Be aware direct query will need to refresh and so will be slightly slower.

Publishing

Once you have completed the modelling and visuals, you can publish the report. You need to check the credentials of the report. Even if credentials look okay, confirm the viewers credentials are used. In the workspace, open up settings of the dataset. Under Data source credentials click on Edit credentials. Authentication method should be OAuth2 and select the appropiate security level.

If you are using direct query then tick the bottom option so that report viewers credentials get used to fetch the data. Security within Dataverse is now applied to your report.

Click Sign in and complete the sign in to now make your report ready for the report consumers.

Conclusion

Dataverse is a great data source for business apps and being able to report on the data in there is important. Building a simple efficient pattern to do this is important. Hopefully this post helps get you there.

Power BI Series

Power BI – Switch Dataverse Tenancy

Tue, 01 Nov 2022 12:47:36 +0000

Connecting to Dataverse with Power BI to report on the business data is becoming easier and more common. One difference with connecting to Dataverse is there are two connectors involved. One to list the available environments and the second to connect to the data. Occasionally you need to change to point to a different tenancy which means changing the first connector to switch Dataverse tenancy.

YouTube version

Starting Point

When I click Dataverse on the Home ribbon the navigator shows me where I last connected. I need to connect to a different tenancy for this report.

Switch Dataverse Tenancy

You need to change the login for the Dataverse login. From the Home ribbon, click the down arrow on Transform data and select Data source settings. In the Data source settings dialog select Global permissions. Then select Dataverse and select Edit Permissions.

In the Edit Permissions dialog click on the Edit button. This will prompt you to login to the different tenancy. If you do not have a Privacy Level selected I recommend you select one, often Organizational will fit most data sources. It will depend upon your company’s policy.

Result

Now when I click on the Dataverse button I get the list of environments on the different tenancy.

The Dataverse connector is only used to populate the Dataverse Navigator window. Switching the tenancy will not break any other reports. If all you do is report from one tenancy you will never have to do this. Though I’ve been asked to explain this multiple times.

Power BI Series

Power BI & Dataverse – Choice Columns

Sat, 24 Sep 2022 19:24:07 +0000

Choices and Choice Column Introduction

When a choice column is created in a Dataverse table the developer can either select a pre-made list of choices or create a custom list of choices. In a Power BI model it helps to add the dimension table of those values.

The difference between a choice and choices column is how many choices can be picked. A choice column only allows one choice and a choices columns column allows multiple values to be added. So if we take dish from our menu then the menu section, eg starter, main, side would be a choice but the allergens such as gluten, dairy etc could be a choices column.

Choice Column in Power BI

When the table is loaded into Power BI there are two columns for the choice column. The first column is the number that refers to the choice in the choices list and the second column is the value from the choice list. The limitation of using the name column is only selected values will in your data and it will slow down the refresh of the data.

Choices Column in Power BI

When the table is loaded into Power BI there is a single column for the choices column. This column contains numbers separated by commas. Each of these numbers refers to a choice in the choices list. Using the Dataverse connection, there is no easy to get the choice values.

Using the Web API to get choice lists

Choice are part of the table and columns definition and one of the four paths exposed is Global Option Set Definitions. Choices and Options are the same thing in this context. Microsoft give us the path on this page

https://docs.microsoft.com/en-us/powerapps/developer/data-platform/webapi/use-web-api-metadata

The path given is

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[Organization URI]/api/data/v9.0/GlobalOptionSetDefinitions

If you navigate to that url in your environment you will get JSON data. Then exploring the JSON we can find the Name of the choice list. Expanding Options we get the Value which matches the values in the choices column in our table. Expanding Label and then UserLocalizedLabel we get the Label value.

Using the Web Connector to link to the JSON we can connect. Power Query decides to expand everything for you. I deleted all the steps except Source and expanded only the columns I needed.

Before I add the list I create a parameter called Environment to store the path to the my Dataverse environment, eg orgdaae212f.crm11.dynamics.com.

Then this code gives you the list of all the choice lists in your environment. I save this as one query which is not loaded and then I add referenced queries for each choice list that I want to include in my report.

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let
 Source = Json.Document(Web.Contents("https://" & Environment & "/api/data/v9.0/GlobalOptionSetDefinitions")),
 value = Source[value],
 #"Converted to Table" = Table.FromList(value, Splitter.SplitByNothing(), null, null, ExtraValues.Error),
 #"Expanded Column1" = Table.ExpandRecordColumn(#"Converted to Table", "Column1", {"Name", "Options"}, {"Name", "Options"}),
 #"Expanded Options" = Table.ExpandListColumn(#"Expanded Column1", "Options"),
 #"Expanded Options1" = Table.ExpandRecordColumn(#"Expanded Options", "Options", {"Value", "Label"}, {"Value", "Label"}),
 #"Expanded Label" = Table.ExpandRecordColumn(#"Expanded Options1", "Label", {"UserLocalizedLabel"}, {"UserLocalizedLabel"}),
 #"Expanded UserLocalizedLabel" = Table.ExpandRecordColumn(#"Expanded Label", "UserLocalizedLabel", {"Label"}, {"Label"}),
 #"Changed Type" = Table.TransformColumnTypes(#"Expanded UserLocalizedLabel",{{"Name", type text}, {"Value", Int64.Type}, {"Label", type text}}),
 #"Renamed Columns" = Table.RenameColumns(#"Changed Type",{{"Name", "Choice List"}, {"Value", "Choice Value"}, {"Label", "Choice Name"}})
in
 #"Renamed Columns"

Result

After you add the above code, you get a table of all the options available. Then using reference and a filter and the choice dimension tables can be created.

Conclusion

Its not pretty, its not clean and I’d prefer a straight forward connector. It works for now though and until there is another method that works this is the method I’ll use. If there is another method please correct me via the comments below and I’ll correct my post!

Power BI Series

Power BI Dataverse Connector – July 2022 Update

Thu, 01 Sep 2022 16:33:32 +0000

In the July 2022 Power BI update, they updated the Dataverse connector. The connector now uses the display names from a Dataverse table. Dataverse columns have internal name and display names and previously the display names were not available.

YouTube Version

For those who prefer a video version.

New Connection

Let’s start with a brand new Dataverse connection. When you click on the Dataverse button the dialog appears as before. When you select a table it still shows the internal names of the columns.

When you click Transform and Power Query opens it still shows the internal names. So I select a few columns and then click Close and Apply. When the data appears in Power BI desktop it now shows the display names. If a column does not have a display name such as statecodename it shows the internal name.

Power Query and Power BI Desktop views

When I experimented I found that even if you renamed the columns within Power Query the name within Power BI desktop did not change. And if you changed the name in Power BI desktop it did not push back into Power Query as it does with other connectors.

Exploring with Tabular Editor

Opening the model in Tabular Editor 2 we can see that the column has two names. So the source column has a different value to the Name property.

Updating an Existing Model

I created a Power BI model in an earlier version of Power that used the old Dataverse connector. It contains the Account table with columns renamed in Power Query and a measure to count the Account table records.

Report before refresh

When I opened the file in the July 2022 version of Power BI with the new Dataverse Connector, it looked unchanged. When the report is refreshed in Power BI desktop the connector is updated. The column names change and measures update and still work.

Report after refresh with updated column names

Exceptions

If the table from Dataverse is transformed using a reference the display names do not come through. I have not explored all the combinations as to which break the new update so please be aware.

Conclusion on Dataverse Connector

The update to the dataverse connector makes this connector work differently to other connectors. This update works well if all the transformation does is reduce the columns and filter the rows. This will work for many reports.

Dataverse on Hat Full of Data

Microsoft Fabric – Using Copy Job with Dataverse

Table of Contents

Scenario

First Copy Job – Dataverse Connector

Create Copy Job

Choose Data Source

Choose Data

Choose Data Destination

Choose copy job mode

Map to destination

Review + save

Copy Job Run

Copy Job using SQL Server connection

New Copy Job using SQL Server

Choose Data

Incremental and Merge setup

Save, Review and Schedule

Incremental and Merge Running

Trouble Shooting

Alternative Options to using Copy Job with Dataverse

Link to Microsoft Fabric

Conclusion

Power Platform Solution and Power BI – Part 3

Series

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Embed the report into a form.

Filtering the embedded report.

Testing the form

Conclusion

More Power BI Posts

Power BI Series

Power Platform Solution and Power BI – Part 2

Intro – Add a Dashboard

Series

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Create the Dashboard

Add the Dashboard to the App in the Power Platform Solution

Note

Testing the Report

Conclusion

More Power BI Posts

Power BI Series

Power Platform Solution and Power BI – Part 1

Series

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Preparation

Add Power BI to Power Platform Solution

Checking the New Workspace

Finishing the connection part

Conclusion and Resources

More Power BI Posts

Power BI Series

Using SQL on Dataverse for Power BI

YouTube Version

Microsoft SQL Server Management Studio

Write your first query

SQL Code

Filtering the data

Using SQL on Dataverse in Power BI

Permission to Run a Native Database Query

Loading into Power BI Desktop

Publishing

Conclusion

More Power BI Posts

Power BI Series

Power BI – Switch Dataverse Tenancy

YouTube version

Starting Point

Switch Dataverse Tenancy

Result

More Power BI Posts

Power BI Series

Power BI & Dataverse – Choice Columns

Choices and Choice Column Introduction

Choice Column in Power BI

Choices Column in Power BI

Using the Web API to get choice lists

Result

Conclusion