Now that we have got Power BI Premium per User (PPU), this opens a whole host of new capabilities.

In this blog post I am going to demonstrate how to make a granular deployment where I will create a new column in my City table, and only deploy those changes.

What this means is that by deploying only the column change to my PPU dataset, I am only updating the column in the table.

This now saves me from doing the following tasks previously:

• Time taken to refresh the PBIX file so that the data is up to date.
• Re-uploading my PBIX.
• If configured re-creating the incremental refreshing
• Time and effort to upload and wait for dataset refresh.
• Quick updates to my dataset.

I will not have to worry about saving my PBIX file, file and if configured re-creating the incremental refreshing. This saves me a lot of time and effort.

Separating dataset and report

The first thing that I want to mention it is always recommended to separate the dataset and report.

You might be thinking why the separation?

Some of the reasons are:

• People curating and updating the dataset can do this independently.
• People creating reports and dashboards can create this independently.
• Quicker and easier deployment of changes to datasets without affecting the reports.
• Reports can be updated without having to rely on dataset updates.

Updating my existing PBIX file by adding a new column

In this example I am now going to add a new column called “City-State Province” to my City table

• As you can see below, I have my existing table.
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• I then went into Power Query and added the new column City-State Province
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• I could then see the column in my table.
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• I then saved my PBIX file.

Using the ALM Toolkit to compare and deploy the granular changes to my PPU Dataset

I am now at the point where I can now deploy only the changes, I want to deploy using the ALM Toolkit.

Changing the default Options for ALM Toolkit

After installing ALM Toolkit what I like to do is to change the default options which I think is the best.

What I do is to ensure I have got the following options enabled as shown below

The main option here is the “Processing Option”, where I set this to “Do Not Process”, this ensures that when I complete a deployment it will deploy the changes. I will then have to go in manually and process the affected tables.

I prefer this option because it allows for a much quicker deployment and allows me to process the affected tables when I am ready to.

NOTE: You can download the ALM Toolkit here: ALM Toolkit

Deploying the changes

• I had already installed the ALM Toolkit.
• In Power BI Desktop I went to External Tools and selected ALM Toolkit
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• I am then presented on what I want to compare.
  • In my example I am comparing my PBIX file to my dataset in the PPU App Workspace as shown below.
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  • NOTE: When I click on the Dataset it then prompts me to log in and authenticate.
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  • I then clicked Ok, and the comparison began.
  • By default, after the comparison is complete it will show all actions.
    • ACTIONS options are Update to Update, or Skip to skip the action.
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  • What I typically do is to click on the drop down under Select Actions and select “Hide Skip Objects”, this makes it easier for me to see what update actions there are.
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  • Now, I can see that my City table is left, and it has got the action set to Update.
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  • What I can now also do, is if I look at the bottom of the screen there is a comparison to show me where the changes are.
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  • If you look at the bottom right-hand side you will see that I have highlighted there is a green section next to a red section.
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    • This is showing where there is a difference.
  • Scrolling down I can then see the new column that has been added to the table.
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  • When I scroll down to the end, I can then see what those differences are for the Power Query for the table, as shown below I can see my new column that was added.
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  • Next, I clicked on Validate Selection, this is where it validates everything to make sure it can be deployed.
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  • Based on the options I have selected to show me warnings and informational messages, which is displayed as shown below.
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  • The option to Update is now available.
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  • I do have other things I could such as Generate script or Report differences, but I will leave that to another blog post.
  • I click on Update, and then get a prompt asking me if I am sure I want to update the target.
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    • Of course, I want to! And I click Yes.
  • Once the deployment is complete, I can then see it was successfully deployed.
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  • I was then prompted if I want to refresh the comparison.
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  • I clicked on No because I know what has been deployed.
  • I then checked in the Power BI Service and I can see the update column.
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Processing the affected table

The final step was for me to now process the affected table, which would allow the column [City-State Province]

To do this I can refresh this using SQL Server Management Studio (SSMS) or refreshing the dataset via the Power BI Service.

I am going to show you how I did this using SSMS.

• I went into SSMS, found my database, then table.
• I right clicked on the table and selected Process Table.
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• I then changed Mode to “Process Full” and made sure that City was selected as shown below.
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  • I then clicked on Script, which then scripts it into an SSMS Query window
    • I do this, because it allows me to view the entire processing details and if there is an error I will be able to see it in the text.
  • I then clicked on Execute.
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  • When the processing is completed, I then see the following in the messages below.
    • NOTE: Currently there is a bug when using SSMS with the following screen shot below, it will still be successful and complete the processing of the table
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  • Once completed this is what the Results look like
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• I then go back and validate my data and I can see the updated column with values as shown below.
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Summary

In this blog post I have demonstrated how to complete a granular deployment of a new column to a PPU dataset.

I hope that you found this useful.

I am thinking of creating a similar guide on how to create or update an existing measure to a PPU dataset without having to publish the entire dataset. If this is something you feel will be of value please let me know.

Thanks for reading