Business Intelligence - BI, DAX, Power BI, Power BI Desktop, Power BI Desktop RS, Self-Service BI

How to Define A Measure Table in Power BI Desktop

In this post I show you a simple trick to make your Power BI model more organised and more readable. I call it creating a “Measure Table”. Let me explain. The story is that I was working on a model with lots of tables. The database schema was NOT a proper star schema so there were a bunch of measures spread into lots of different tables. On top of that we’ve created lots of calculated measures with different home tables which made it really hard to find a particular measure or calculated measure. I thought, well, when it is that hard to find the calculated measures at development time how hard it could be for a customer to find, understand and use the measures we created. The visibility of the calculated measures could be an issue when we have lots of measures in lots of different tables. You will soon feel the issue in customer training sessions when you need to navigate between lots of different tables to find a calculated measure.

Consider you create a Power BI model with direct connect to a SSAS Multidimensional instance. You will immediately notice that all measure groups have a special calculation icon () rather than a normal table icon () which makes the measure groups more recognisable for the end users. For instance, you can easily find any calculated measure related to “Internet Sales” under the “Internet Sales” measure group.

I know, we can search and find the measures very easily, but, our model would be more organised and more user friendly if we can put all measures in one or more tables which contain just related calculated measures and nothing else. For instance, we can create a measure table for time intelligence calculations and name it “Sales Time Intelligence Measures” and put all calculated measures like “Sales YTD”, “Sales LYTD”, “Sales Period Over Period” on it. It will make your model nice and clean, easy to use and easy to learn for your customers. It will also help you to train your customers more easily.

In this article I’ll connect to a SQL Server instance and will use the famous Adventure Works database. I also show you how to get the job done in both “Import” and “DirectQuery” modes as there are some limitations applied to the DirectQuery mode which makes it harder to do what we want.

Lets start.

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Data Warehousing - DW, DAX, Power BI, Power BI Desktop, Power Pivot

Side-by-side Role-Playing Dimensions In Power BI

Role-playing dimension is one those concepts that is discussed a lot from time to time. I also posted an article about implementing role-playing dimensions in Tabular models.

To recap, in the role playing dimensions in SSAS Tabular article I explained three different solutions:

Importing role playing dimensions several times into the model
Creating database views in the source side (in case your source is a from of RDBMS like SQL Server, Oracle etc…) then import the data into the model
Keep the inactive relationships in the model and create several measures to take care of different roles using USERELATIONSHIP functions in DAX

I this post I explain implementation of the third option above. In this scenario you need to create especial calculated measures based on the roles you have in a fact table. One the most common role-playing dimensions is Date dimension. Consider you have to show Internet Sales Amount by Order Date, Due Date and Ship Date in a single chart in your report. In this case, having 3 different date tables won’t help us to achieve the goal.

New to Power BI? Quickly learn about Data Visualisation in Power BI here.

Defining new Measures in Power BI Desktop

Basically, what I’m going to explain in this post is using inactive relationships between FactInternetSales table and the DimDate dimension by adding a new Calculated measure. In this case, we’ll be able to show Sales Amount by different roles, well, dates in this sample in a single chart.

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DAX, Power BI, Power BI Desktop, Power Pivot, Power Query, Power View

What is new for BI in Excel 2016

It’s been awhile that we are waiting for a sensible improvements in Microsoft self-service BI. The good news is that finally there will be some cool new features added to the next version of Excel which is Excel 2016. By some, I mean, well, there not a lot new BI features, but, some. Something is better than nothing, not too bad though!

Integrating BI features with Excel:

Power View and Power Map:

As you know, Power Pivot was integrated as a built-it feature to Excel 2013. Now I’m really happy that the same thing happened to Power View and Power Map. So you don’t need to install them separately. You can now turn these features on from:

File–> Options–> Advanced-> (scroll down the page) Data-> Enable Data Analysis Add-ins: Power Pivot, Power View, and Power Map