Category: Analysis Services

Kasper de Jonge walks us through calculation groups:

In most cases the business wants to see some common calculations done over these measures like YTD, QTD, YoY% etc. That means you must make a new measure for each of the calculation over the base measure. This leads to measure explosion in your model as you need to add a new measure for each variation. Very quickly this leads to not four measures but sixteen and more creating a management headache.

In come calculation groups. With calculation groups you can create a group that can apply common calculation over base measures. It’s hard to explain so let’s just dive in on how that works.

Click through for a demo of how to enable and use calculation groups.

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Marco Russo takes us through the different types of relationships we might encounter in Power BI and Analysis Services Tabular models:

A relationship can be strong or weak. In a strong relationship the engine knows that the one-side of the relationship contains unique values. If the engine cannot check that the one-side of the relationship contains unique values for the key, then the relationship is weak. A relationship can be weak either because the engine cannot ensure the uniqueness of the constraint, due to technical reasons we outline later, or because the developer defined it as such.

A weak relationship is not used as part of table expansion. Power BI has been allowing composite models since 2018; In a composite model, it is possible to create tables in a model containing data in both Import mode (a copy of data from the data source is preloaded and cached in memory using the VertiPaq engine) and in DirectQuery mode (the data source is only accessed at query time).

There is quite a bit of useful information in here.

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Chris Webb shows how you can improve performance of Excel pivot tables hitting Analysis Services Multidimensional models:

Back in 2016 I wrote the following blog post about changes to the way Excel 365 generated MDX queries for PivotTables connected to Analysis Services, Power Pivot/the Excel Data Model and Power BI datasets:

https://blog.crossjoin.co.uk/2016/07/08/excel-2016-pivottable-mdx-changes-lead-to-big-query-performance-gains/

I know it sounds boring and not something you need to worry about but trust me, this is important – these changes solved the vast majority of Excel PivotTable performance problems that I encountered when I was a consultant so you should read the above post before continuing.

Unfortunately, earlier this year these changes had to be partially rolled back because in some rare cases the queries generated returned incorrect results; this means that you may find that values for subtotals and grand totals are again being returned even when they aren’t being displayed. The good news is that you should still be able to get the improved performance with a few minor tweaks.

Read on to see what those tweaks are.

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Kasper de Jonge uses Power BI to figure out which columns are being used in an SSAS Tabular model:

I got an interesting question about being able to figure out which measures and columns are being used for all tabular models in a server, either by known reports or by self service users using Power BI. To solve this I decided to use Power BI :).

To get the required information I decided to capture and parse the queries being that are being send to AAS and parse the results Power BI desktop over a period of time. In this post I describe how to do it.

Check it out, and also read the comments for an additional tip from Bill Anton.

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Dustin Ryan digs deep into the bag of tricks:

Last week I was asked to tackle a requirement by a customer adopting Analysis Services to enable data exploration and ad hoc analysis by their users. One of their requirements was to secure columns based on a grant related to a cost center. For example, a grant has several attributes, with some attributes being considered “sensitive” and other attributes considered “non-sensitive”. Non-sensitive grant attributes would accessible to all users while a subset of the attributes in the grant table considered “sensitive” would be accessible to users related to the corresponding cost center. The challenge here is that while Analysis Services supports column level security, dynamic column level security is not supported. So my colleague and friend, the great Steve Pontello, and I put our heads together to address the requirement.

Read on to see how they did it and the resulting solution’s limitations.

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