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Category: Analysis Services

Migrating Azure Analysis Services to Power BI Premium

Gilbert Quevauvilliers dumps AAS:

I thought it would be a good idea to walk through the steps when looking to migrate AAS to PBI.

In the past when I had to do this for clients it was a lot of manual steps and a lot of small things to get just right. This process is now seamless and awesome!

Reviewing Gilbert’s step-by-step process, yeah, this is easy, though watch out for the pitfalls Gilbert found.

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Tracking Power BI Desktop Activity in SQL Server

Chris Webb looks in on things:

Something I do all the time when performance tuning Power BI is use SQL Server Profiler to monitor query and refresh activity. There’s a handy external tool that lets you open up Profiler with a connection to Power BI Desktop; if you’re using Power BI Premium you can also connect Profiler up to a published dataset using the XMLA Endpoint. Profiler is a bit old-school though and likely to lead to snarky comments from SQL Server DBAs (it’s not deprecated for Analysis Services though!) who’ll say you should be using Extended Events (aka xEvents) instead. And guess what – did you know you can use Analysis Services xEvents to monitor activity in Power BI Desktop?

It’s the power of Extended Events.

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Releasing a Tabular Model without Users or Roles

Olivier van Streenlandt hit a deployment problem:

A couple of weeks ago my team & I ran into an issue with SQL Server Analysis Services (SSAS), due to a network split between companies, We weren’t able anymore to manage our SSAS access into our SSAS Tabular Model. Since deploying a Tabular Model using Visual Studio is also overwriting members & roles, we needed to find a valid alternative to execute our deployments. Manually at first and automated in the end.

Read on to see how they used Azure DevOps pipelines to solve the issue.

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Power Automate and Dataset-Driven Power BI Subscriptions

Dan English follows up on a prior topic:

In the last post I went over using Power Automate to perform a data driven report subscription using a Paginated report referencing an AAS database. The flow referenced an Excel file with the information to make the process data driven and generate 2000 PDF files that could then be emailed to users. In the flow the PDF files were simply placed in a OneDrive folder for testing purposes to validate the flow would run as expected and to review the metrics after the fact to evaluate the impact of running the process.

For the follow up there were two items that I wanted to compare against the original flow

1. Moving the AAS database being referenced to a Power BI dataset hosted in the same capacity as the Paginated report

2. Using a Power BI report instead of a Paginated report

In this post I will cover the first comparison. 

Check out what changes and what stays the same between using Azure Analysis Services and Power BI-hosted datasets.

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Object-Level Security in Power BI and Analysis Services

Marco Russo and Alberto Ferrari take advantage of object-level security:

To be more technical, object-level security can be applied to tables and columns, but it cannot be applied to measures directly. If a measure – whether in a direct or indirect way – references a column or a table that is not accessible under the current security context, the measure becomes invisible as well. This way, it is guaranteed that if a column must be invisible to a group of users, its content cannot be inferred by looking at the result of measures based on said column.

Concretely, there may be cases where a measure should be hidden from a group of users without removing the visibility of existing data structures. Let us look at a simple example first. We define the Sales Amount measure as the product of Sales[Quantity] by Sales[Price]. You also have a Discounted Sales measure that applies a set discount Sales Amount; now how can you hide Discounted Sales from a group of users without hiding the initial Sales Amount measure? By hiding either Sales[Quantity] or Sales[Price], you would hide both measures. Because the discount is set inside the Discounted Sales measure and not stored in the model, it looks as though you cannot hide just the measure. However, it we create a dependency in Discounted Sales on an empty hidden table specifically created to generate that dependency, we can hide Discounted Sales by hiding that table.

Read on to see how.

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Making the Case for Azure Analysis Services

Teo Lachev makes the case:

Microsoft BI practitioners have three options for hosting semantic models: SSAS (on prem), Azure Analysis Services (cloud), and Power BI (cloud). AAS is somewhat caught between a rock and a hard place. Given that Power BI gets the most attention for cloud deployment, why would you consider AAS at all? There are two main reasons:

Read on for the reasons. Knowing how much it does cost, it almost feels like trying to thread a needle: if you don’t spent enough or have enough data, Power BI is typically much more efficient; if you have sufficient data, I’d want to do a proper cost analysis between on-prem (or IaaS) Analysis Services and Azure Analysis Services.

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Handling Merge Conflicts with SSAS Tabular Projects

Richard Swinbank fights Visual Studio:

I sometimes find working with Visual Studio’s projects a challenge in multi-developer environments, because each project type seems to have its own vulnerability to Git merge conflicts. In the case of SSAS tabular, I’ve found two issues to be a regular source of conflicts:

Click through to see what those two causes are and what you can do to reduce the risk of having either one burn you.

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Switching Connections from AAS to Power BI

Marc Lelijveld wants to swap a connection from using Azure Analysis Services to Power BI Premium:

Having the context of an Azure Analysis Services dataset that is migrated to Power BI Premium, you might have to rebind many reports. Especially if this dataset is positioned as being a managed dataset that is also used for self-service purposes and has many related reports.

In this blog I will elaborate on how you can easily rebind all these reports to the new Power BI dataset, without downloading all reports and manual rebinding.

It’s not a trivial operation, but it is a lot easier than updating each entry individually.

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Comparing Azure Analysis Services and Power BI PPU on Cost

Gilbert Quevauvilliers hits on an important factor:

One of the most important aspects when looking to migrate from AAS to PPU is what will costs be. This plays an important part in the decision.

In this blog post instead of doing an AAS and PPU comparison I am going to do this side by side, which I feel will make it easier to compare.

In my opinion it is only fair to compare the same sizing between AAS and PPU, and this can only be done by using the Memory allocation.

Click through for the analysis.

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