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«November 2015»

DirectQuery in Power BI Desktop

In the latest Power BI Desktop a new Preview features was released that now allows you to connect using DirectQuery to either SQL Server or Azure SQL Databases.  DirectQuery is a really neat feature that allows you to point to the live version of the data source rather than importing the data into a data model in Power BI Desktop. 

Normally when you want to get an updated dataset in the Power BI Desktop you would have to manually click the refresh button (this can be automated in the Power BI Service), which would initiate a full reimport of your data.  This refresh could take a variable amount of time depending on how much data your have.  For instance, if you’re refreshing a very large table you may be waiting quite a while to see the newly added data. 

With DirectQuery data imports are not required because you’re always looking at a live version of the data.  Let me show you how it works!

Turning on the DirectQuery Preview

Now, because DirectQuery is still in Preview you must first activate the feature by navigating to File->Options and settings->Options->Preview Features then check DirectQuery for SQL Server and Azure SQL Database


Once you click OK you may be prompted to restart the Power BI Desktop to utilize the feature.

Using DirectQuery in Power BI Desktop

Next make a connection either to an On-Premises SQL Server or Azure SQL database.

Go to the Home ribbon and select Get Data then SQL Server.


Provide your Server and Database names then click OK. ***Do not use a SQL statement.  It is not currently supported with DirectQuery***


From the Navigator pane choose the table(s) you would like to use.  I’m just going to pick the DimProduct table for this example and then click Load.  You could select Edit and that would launch the Query Editor where you could manipulate the extract.  This would allow you to add any business rules needed to the data before visualizing it.


Next you will be prompted to select what you want to connect to the data. Again, Import means the data

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The Big Data Blog Series

Over the last few years I’ve been speaking a lot on the subject of Big Data. I started by giving an intermediate session called “Show Me Whatcha’ Workin’ With”. This session was designed for people who had attended a one hour introductory session that showed you how to load data, to look at possible applications … Continue reading The Big Data Blog Series
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Hierarchy Types in SSAS

  • 22 July 2010
  • Author: kylewalker
  • Number of views: 29831

One of the most powerful tools in the BI stack is the SSAS cube.  The cube is a collection of related dimensions and measures that, once completed, can provide an enormous about of data that can be sliced just about any way you want it...  Oh, and it'll do it just as fast as you can click your mouse.  Now like I said, within a cube there are dimensions.  These are a lot like the ones you'll see in your data warehouse.  A lot of times, within dimension, you'll find hierarchies.  Hierarchies are logical entities that an end user can use to analyze fact data.  These entities can be made of one or multiple levels and can manifest itself in one of three ways: balanced, unbalanced, or ragged.

A balanced hierarchy is one that all of the branches of the hierarchy reach to the same level and each member's parent belongs to the level immediately above it (no gaps in levels).  One common example of a balanced hierarchy can be found in a date dimension.  Here is an illustration of what I'm talking about:

Date Dimension

As you can see, all of the branches reach an equal length and there are no gaps in levels.

The second type of hierarchy is unbalanced.  In an unbalanced hierarchy, all of the branches of the hierarchy don't reach to the same level but each member's parent does belong to the level immediately above it.  One example of this type of hierarchy is an employee hierarchy.  There may be some positions on the same level that don't have direct reports, while others do.  Here is an illustration:

Employee Dimension

The last type of hierarchy is called ragged.  In a ragged hierarchy, each level has a consistent meaning from branch to branch, but one or more branches might have a missing level.  An example of this may be a geography hierarchy, as seen below.

Geography Dimension

I hope this sheds some light on the different types of hierarchies you'll be working with on your next SSAS project.

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