What Does XMLA Endpoints Mean for Power BI and How to Test it for Free?

Test Environment from Power BI XMLA Endpoint

XMLA endpoint connectivity for public preview has been announced late March 2019. As at today, it is only available for Power BI Premium capacity users. This sounds like a massive restriction to a lot of people who don’t have a Premium capacity, but they’d love to see how it works. In this article I show you an easy way to get your hands to Power BI XMLA endpoint as quick as possible. Before I start, I’d like to simply explain what XMLA endpoint is and what it really means for Power BI users.

Power BI is Like Onion! It has layers!

Generally speaking, Power BI has two different layers, presentation layer and data model layer. Presentation layer is the visual layer, the one you make all those compelling reports and visualisations. The data model as the name resembles, is the layer that you make your data model in. This layer is the one you can access it via XMLA connectivity.

In a Power BI Desktop file, you can see both layers:

Different layers of Power BI

How XMLA Relates to Different Layers in Power BI?

As you may have already guessed, XMLA is only related to the data model layer and it has nothing to do with the presentation layer. So you may connect to a data model, browse the data model, import data from the model to other platforms like Excel and so forth.

XMLA Is Not New!

Seriously? Yes, seriously. It is not new. It’s been around for many years and perhaps you’ve already used it zillions of times. Whenever you’re connecting to an instance of SQL Server Analysis Services, either Multidimensional or Tabular from any tools like SQL Server Management Studio (SSMS), Power BI Report Builder, Excel, Tableau, etc…, you’re using XMLA connectivity indeed.

Power BI is an Instance of SSAS Tabular

It is true. Power BI runs a local instance of SSAS Tabular model. So, whenever you open a Power BI Desktop file (PBIX), Power BI creates a local instance of SSAS Tabular model with a random local port number that can be accessed on your local machine only. When you close the file, the local instance of SSAS Tabular is shut down and its port number is released.

I first revealed the fact that you can connect to the underlying data model in Power BI Desktop from whole different range of tools like SSMS, SQL Server Profiler, Excel, etc… on Jun 2016. So, we indeed were using XMLA to connect to Power BI data models for a long time. We can even take a step further to import our Power BI data models into an instance of SSAS Tabular. In that sense, we are literally generating XMLA scripts from Power BI to create the same data model in SSAS Tabular. How cool is that?

Sooo… What is new then?

Continue reading “What Does XMLA Endpoints Mean for Power BI and How to Test it for Free?”

Quick Tips: How to Filter a Column by another Column from a Different Query in Power Query

Filter a Column by a Column from a Different Query in Power Query

A while ago I was visiting a customer that asked if they can filter a query data by a column from another query in Power BI. And I said of course you can. In this post I explain how that can be achieved in Power Query. The key point is to know how to reference a query and how to reference a column of that query in Power Query. This is useful when you have a lookup table that can be sourced from every supported data source in Power Query and you want to filter the results of another query by relevant column in the lookup query. In that case, you’ll have a sort of dynamic filtering. So, whenever you refresh your model if new records have been changed in or added to the source of the lookup query, your table will automatically include the new values in the filter step in Power Query.

Referencing a Query

It is quite simple, you just need to use the name of the query. If the query name contains special characters like space, then you need to wrap it with number sign and double quotes like #”QUERY_NAME”. So, if I want to reference another query, in a new blank query, then the Power Query (M) scripts would look like below:

let
    Source = Product
in
    Source

Or something like

let
    Source = #"Product Category"
in
    Source

Referencing a Column

Referencing a column is also quite simple. When you reference a column you need to mention the referencing query name, explained above, along with the column name in brackets. So, the format will look like #”QUERY_NAME”[COLUMN_NAME]. The result is a list of values of that particular column.

let
    Source = #"Product Category"[Product Category Name]
in
    Source
Referencing a Column from Another Query in Power Query
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Quick Tips: Time Dimension with Granularity of Seconds in Power BI and Analysis Services Tabular Models

Quick Tips: Time Dimension with Granularity of Seconds in Power BI and Analysis Services Tabular Models
Photo by Markus Spiske

In an article I posted a while back I showed different methods of creating Time dimension in Power BI and Tabular models. The Time dimension I explained was in Minutes. In this post I show you simple way to create Time dimension supporting Seconds. As this is a quick tip, I only show you how to get the Time and ID columns in the Time dimension. If you need to add time bands (time buckets) check this out for more details.

Time Dimension in Seconds Grain with Power Query (M):

Copy/paste the code below in Advanced Editor to generate Time dimension in Power Query:

let
Source = Table.FromList({1..86400}, Splitter.SplitByNothing()),
#"Renamed Columns" = Table.RenameColumns(Source,{{"Column1", "ID"}}),
#"Time Column Added" = Table.AddColumn(#"Renamed Columns", "Time", each Time.From(#datetime(1970,1,1,0,0,0)+#duration(0,0,0,[ID]))),
#"Changed Type" = Table.TransformColumnTypes(#"Time Column Added",{{"ID", Int64.Type}, {"Time", type time}})
in
#"Changed Type" 
Time Dimension in Power Query

Time Dimension in Seconds Grain with DAX:

Run the DAX expression below in a new calculated Table in Power BI or SSAS Tabular model:

Time in DAX = ADDCOLUMNS(
                       GENERATESERIES(1, 86400, 1)
                        , "Time", TIME(0, 0, 0) + [Value]/86400
                        )
Time Dimension in Seconds Level with DAX
Continue reading “Quick Tips: Time Dimension with Granularity of Seconds in Power BI and Analysis Services Tabular Models”

Exporting Data from Power BI Desktop to Excel and CSV – Part 2: Importing Power BI Data Directly to Excel

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Update 2019 April: If you’re interested in exporting the data model from Power BI Desktop or Power BI Service to CSV or SQL Server check this out.

Note: The method explained in the above post involves Power BI Premium or Embedded capacities with XMLA endpoints connectivity at the time of writing.

In my previous post I explained how to copy and paste data from Power BI Desktop into Excel or CSV. I also explained how easy you can export Power BI Desktop data to CSV using DAX Studio. As I promised, in this post I show you how to import Power BI Desktop data to Excel directly. In this method you don’t need to use any third-party software and the performance is much better than the previous methods.

Note: The method I explain in this post is tested in Excel 2016 only. But, it should work for Excel 2013.

Importing Power BI Desktop Directly to Excel

In one of my previous posts I explained how to connect to a Power BI Desktop from Excel. To import Power BI Desktop data to Excel we have to do the same thing. I explain the way to connect to a Power BI Desktop model directly from Excel, then I show you how to use this method to import Power BI Desktop data.

Finding Power BI Desktop local port number from Power BI Desktop temp directory

We can find Power BI Desktop local port number in number of ways explained here. So in this post I don’t go through all methods.

Whenever we run Power BI Desktop, it opens a random port number. The port number is independent of the model so it doesn’t really matter if  we haven’t connected to any data sources or even if we haven’t open any saved Power BI Desktop (*.PBIX) files. That port number is stored in a text file named “msmdsrv.port.txt”. So the only thing we need is to do is to browse the temp directory of Power BI Desktop and open the “msmdsrv.port.txt” text file. You can find Power BI Desktop temp folder here:

%LocalAppData%\Microsoft\Power BI Desktop\AnalysisServicesWorkspaces

There should be an “AnalysisServicesWorkspaceXXX” folder which XXX is a random number. Open that folder then open “Data” and Find “msmdsrv.port.txt”. Open the file to see Power BI Desktop local port number.

image

Continue reading “Exporting Data from Power BI Desktop to Excel and CSV – Part 2: Importing Power BI Data Directly to Excel”

Exporting Data from Power BI Desktop to Excel and CSV – Part 1: Copy & Paste and DAX Studio Methods

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Update 2019 April: If you’re interested in exporting the data model from Power BI Desktop or Power BI Service to CSV or SQL Server check this out.

Note: The method explained in the above post involves Power BI Premium or Embedded capacities with XMLA endpoints connectivity at the time of writing.

One of the features that is asked a lot on Power BI community is how to export Power BI desktop data to Excel OR CSV.

Note: I’d like to make it clear that in this article we are NOT interested in exporting data from a visual in a report to CSV.

The first question lots of you might have is “How on earth someone wants to export data from a Power BI Desktop model to Excel OR CSV?”.

Power BI brings Power Query, Power Pivot, Power View and Power Map together in one piece of software. So why not using Excel at the first place to load data from the source? There might be lots of other questions about the reasons that someone wants to export data from Power BI Desktop model to Excel (or any other destinations). The reason could be one of the following that someone wants to export data from Power BI Desktop model to other destinations like Excel, CSV, SQL Server etc.

  • For some reason you have just a Power BI Desktop file (PBIX) and you don’t have access to the data sources and you need to provide the data to someone who is not familiar with Power BI
  • You Power BI Desktop consolidates lots of different sources in a single model and it would be very hard to get the same output as you get in Power BI Desktop model in Excel. So an export feature can be super handy
  • You might have done lots of complex transformations in Power BI Query Editor and replication the same logic on the source system could be much more complex and time consuming, so again exporting data from a current Power BI Desktop model makes sense
  • You have a bunch of calculated columns created in DAX and you don’t want to go back and redo all the hard works you have already done in Power BI in another environment like Excel
  • You might want to use the current Power BI data in Cortana Analytics
  • You are just curious to see if it is possible
  • None of the above!

But, the reality is that regardless of the reason, lots of people still want to export data from Power BI Desktop to different destinations. So let’s have a look at different workarounds until this feature is not available in Power BI. I’ll explain different ways to export Power BI Desktop data in a series of articles. In this post you learn how to copy Power BI Desktop data to a destination file like Excel or CSV without any third-party software involved. I also explain how easy you can export Power BI Desktop data to CSV using DAX Studio.

Copy Data from Data View in Power BI Desktop and Paste it to Destination

The easiest workaround is simply copy/paste data from Data view in Power BI Desktop.

  • Open your Power BI Desktop model
  • Switch to Data view by clicking on Data tab

2017-03-02 15_12_09-AW, Internet Sales - Power BI Desktop.png

You have now 3 options to copy data:

Continue reading “Exporting Data from Power BI Desktop to Excel and CSV – Part 1: Copy & Paste and DAX Studio Methods”

Use KPI in Table, Matrix and Card Visualisations in Power BI

Use KPI in Table, Matrix and Card Visualisations in Power BI

One of the coolest features in Power Pivot is the ability to define KPIs based on calculated measures. You can create KPIs in SSAS Tabular as well. Unfortunately, this feature is missing from Power BI. In this post I show you a very simple way to import KPIs and use them in Table, Matrix, Multi-row card and Card visualisations in Power BI.

I use the word “IMPORT” as this feature is NOT available in Power BI Desktop yet so we CANNOT create KPIs directly in Power BI Desktop, but, there is work around for it that I explain it in this post.

Requirements

  • Latest version of Power BI Desktop
  • Microsoft Excel (2007 or later)
  • Power Pivot add-on if using Excel 2007 to 2013 (Power Pivot is already available in Excel 2016)
  • Power Query add-on if you need to transform your data (Power Query is available only in Excel 2010 Professional Plus and Excel 2013. It’s added to Excel 2016 as a built-in feature. Check this out to find out more about BI features in Excel 2016.). In this post I’m not loading data using Power Query, so you can ignore Power Query if you want to follow this article to make your first sample KPI work.

How It Works

The work around is really easy. You only need to

  • open Excel
  • load data into Power Pivot model from your source
  • create desired calculated measures in Power Pivot
  • create desired KPIs on top of your calculated measure(s)
  • save the Model (Excel file)
  • import the Model to Power BI Desktop

Let’s go through the whole process step-by-step to see how it works on real world.

Note: I use Excel 2016 and Adventure Works DW SQL Server sample database. If you’re using prior versions of Excel, you have to download and install Power Pivot for Excel. All steps below are pretty much the same.

  • Open Excel 2016
  • From Data tab click “Manage Data Model”

Excel 2016 Manage Data Model

Note: In case you’re using prior versions of Excel you need to click “Manage” from Power Pivot tab. All other steps would be the same.

  • Get external data from SQL ServerPower Pivot Get External Data From
  • Enter server name and database name then click Next

Power Pivot Get Data From SQL Server

  • Select “FactResellerSales”, “DimProduct”, “DimProductCategory”  and “DimProductSubCategory” then click Finish

Power Pivot Get Data From SQL Server

  • After the data successfully imported click Close

Power Pivot Get Data From SQL Server

Continue reading “Use KPI in Table, Matrix and Card Visualisations in Power BI”