Category Archives: Business Intelligence

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Excel Tip #29: Forcing Slicers to Filter Each Other when Using CUBE Functions

As I mentioned in my original post, Exploring Excel 2013 as Microsoft’s BI Client, I will be posting tips regularly about using Excel 2013 and later.  Much of the content will be a result of my daily interactions with business users and other BI devs.  In order to not forget what I learn or discover, I write it down … here.  I hope you too will discover something new you can use.  Enjoy!


You have went to all the trouble to build out a good set of slicers which allow you to “drill” down to details based on selections. In my example, I have created a revenue distribution table using cube formulas such as:

=CUBEVALUE(“ThisWorkbookDataModel”,$B6, Slicer_Date, Slicer_RestaurantName, Slicer_Seat_Number, Slicer_TableNumber)


Each cell with data references all the slicers. When working with pivot tables or pivot charts, the slicers will hide values that have no matching reference. However, since we are using cube formulas the slicers have no ability to cross reference. For example, when I select a date and a table, I expect to see my seat list reduce in size, but it does not. All of my slicers are set up to hide options when data is available. There are two examples below. In the first, you can see that the seats are not filtered. However, this may be expected. In the second example, we filter a seat which should cause the tables to hide values and it does not work as expected either.



As you can see in the second example, we are able to select a seat that is either not related to the selected table or has no data on that date. Neither of these scenarios is user friendly and does not direct our users to see where the data matches.

Solving the Problem with a “Hidden” Pivot Table

To solve this issue, we are going to use a hidden pivot table. In most cases we would add this to a separate worksheet and then hide the sheet from the users. For sake of our example, I am going to put the pivot table in plain sight for the examples.

Step 1: Add a Pivot Table with the Same Connection as the Slicers

In order for this to work, you need to add a pivot table using the same connection you used with the slicers. The value you use in the pivot table, should only be “empty” or have no matches when that is the expected result. You want to make sure that you do not unintentionally filter out slicers when data exists. In my example, I will use the Total Ticket Amount as the value. That will cover my scenario. In most cases, I recommend looking for a count type value that will always have data if there is a potential match of any kind.


Step 2: Connect the Slicers to the Pivot Table

Using the Apply Filters button on the Pivot Table ribbon, you need to select all the slicers you want to interact with each other.


Once these changes are applied, you will see how my data changed.


Now, let’s test this for real. We will keep the date and table, but now we will see that the other slicers are now filtered to match the data that is available.


As you can see, the solution is fairly simple, but not intuitive. You will be able to create more creative dashboards with this technique. Keep in mind this issue is primarily a problem when using cube formulas in your Excel dashboard.

Until next time…

Using Power BI with HDInsight Part 2: Power BI Desktop and Hive

With the rise of HDInsight and other Hadoop based tools, it is valuable to understand how Power BI can help you take advantage of those big data investments. If you need to set up a cluster to work with, check out my previous posts on Setting Up an HDInsight Cluster and Loading Data Into Your New HDInsight Cluster. These posts show how to do this with no scripting required. If you prefer to script, there are a number of resources with sample scripts on doing the same work.

In this article, I will focus on using Power BI Desktop to get data from the Hadoop file structure in HDInsight using a Hive query. I will also be using the restaurant data I loaded as noted in the previous posts. If you need to create a cluster and load data I encourage you to check the following blog posts:

These posts walk through the process of creating a cluster and loading up data.

Connecting to HDInsight Using the Hive ODBC Driver

Before you can connect using a Hive query you need to download the Hive ODBC Hive from Microsoft.  You can find the driver here: Once you have the driver installed, the connection can be created.

Open Power BI Desktop and click Get Data on the splash screen. This will open the Get Data dialog. Scroll down until you see the ODBC option. (Do not select a Hadoop or HDInsight option. See my previous post on connecting using HDInsight.)


Click Connect to start the process.


Here is where the “fun” begins. You get no help creating a Hive connection string. It took some searching and trial and error to figure out what was needed to make this happen. Here are the properties you need:

  • Driver:  Driver={Microsoft Hive ODBC Driver}
  • Host: (Your HDInsight server name)
  • Port: Port=443
  • Schema: Schema=default (default Hive database schema)
  • RowsFetchedPerBlock: RowsFetchedPerBlock=10000 (This is the default)
  • HiveServerType: HiveServerType=2 (This is the default)
  • AuthMech: AuthMech=6
    • This is the Authentication Mechanism which is Windows Azure HDInsight Service.
  • DefaultStringColumnLength: DefaultStringColumnLength=200 (Default is 32767, this should always be set lower)

Each property is separated by a semicolon. My completed connection string looked like this (Note: I added spaces to fit better in the post.):

Driver={Microsoft Hive ODBC Driver};; Port=443;Schema=default; RowsFetchedPerBlock=10000; HiveServerType=2; AuthMech=6; DefaultStringColumnLength=200;

Enter the connection string into the dialog and then you will be prompted for credentials. Use the Database option and set the Username and Password. Then click Connect. In my case, I see three tables in the resultset including the sample table. We have connected to our HDInsight cluster using Hive.


Retrieving Data from HDInsight Using HiveQL

So, getting a list of tables is not really helpful. As you can see, this is the Power Query portion of the Power BI Desktop. Let’s add a HiveQL statement to return only our sales data.

In Applied Steps, click the gear next to Source. This will reopen the From ODBC dialog. Expand the SQL Statement portion and add a SELECT * FROM yourtable  to get our desired result set. Click Ok and check the results again. You should see the tablename.fieldname format for column headers. At this point, you can proceed with more data shaping and prep data for other analytics. Click Close and Load when you are done and it will load the data into the Power Pivot designer in Power BI desktop.

I hope you enjoyed this series through HDInsight and Power BI. It was a great learning experience for me.

Excel BI Tip #28: Using member expressions in the CUBEVALUE Function

As I mentioned in my original post, Exploring Excel 2013 as Microsoft’s BI Client, I will be posting tips regularly about using Excel 2013 and later.  Much of the content will be a result of my daily interactions with business users and other BI devs.  In order to not forget what I learn or discover, I write it down … here.  I hope you too will discover something new you can use.  Enjoy!


If you have not looked at the cube functions in Excel check out two of my previous posts: Excel BI Tip #18: Using Cube Functions to Break Out of Pivot Tables and Excel BI Tip #27: CUBESET and CUBESETCOUNT Functions. Cube functions allow us to apply MDX functionality in Excel beyond pivot tables and charts. In this post, I will show how you can expand the CUBEVALUE function by directly using member expressions or CUBEMEMBER functions in the syntax. Tip #18 demonstrates how to use cells in Excel.

Typically, you would use these functions separately. For example, CUBEMEMBER is used in column and row headers in a typical solution. Because of this CUBEVALUE usually refers to a series of cells and slicers.

CUBEMEMBER used as a column header:

=CUBEMEMBER(“AdvWorks”,”[Measures].[Customer Count]”)

CUBEVALUE referring to this member:


The snapshot below shows how it looks in Excel when the cell with the CUBEVALUE function is selected:


Using Member Expressions and CUBEMEMBER

The method illustrated above is how the cells are made when a pivot table has been converted to formulas. However, if you look closely the CUBEVALUE function accepts CUBEMEMBER values. The next few examples show how you can use members directly in the name to get more functionality.

=CUBEVALUE(“AdvWorks”, “[Measures].[Customer Count]”,CUBEMEMBER(“AdvWorks”,”[Customer].[Gender].[Female]”))


=CUBEVALUE(“AdvWorks”, “[Measures].[Customer Count]”,”[Customer].[Gender].[Female]”)


You can use any MDX expression that returns a member as one of the expressions in the function. This includes functions like STRTOMEMBER which allows you to create dynamic functions to get current date. Using member expressions allow for even more customization without dependencies on reference columns.

Adding a Slicer

Finally, you can add a slicer reference to the CUBEVALUE function.

=CUBEVALUE(“AdvWorks”, “[Measures].[Customer Count]”,”[Customer].[Gender].[Female]”, Slicer_State_Province)

Excel BI Tip #27: CUBESET and CUBESETCOUNT Functions

As I mentioned in my original post, Exploring Excel 2013 as Microsoft’s BI Client, I will be posting tips regularly about using Excel 2013 and later.  Much of the content will be a result of my daily interactions with business users and other BI devs.  In order to not forget what I learn or discover, I write it down … here.  I hope you too will discover something new you can use.  Enjoy!

CUBE Function Overview

In Tip #18, I talked about the CUBEMEMBER and CUBEVALUE functions which can be used to refer to cube data directly. In this tip, we will look at CUBESET and CUBESETCOUNT. These functions return sets that can be applied to the CUBEVALUE function like the CUBEMEMBER function. They allow you to create custom sets which can be used for calculations such as trailing 12 months, top 10 performers, or the number of customers with sales in 2009. Keep in mind that the advantage of using the CUBE functions with SSAS data is that it allows you to go beyond the limiting capabilities of pivot tables using that data and MDX.

CUBESET Function

The CUBESET function is designed to return a valid MDX Set from the cube or tabular model. The construction of the formula is CUBESET(“connection”,”set expression”,”caption”,”sort order”, “sort by”). Only the connection and set expression are required. However, I highly recommend using the caption. The caption is what will show in the cell with the formula. If you don’t include the caption, the cell will appear empty so you will need mark it in some way. Before I started using the caption, I color coded the cell so I would make sure not to overwrite that cell. In a nutshell, use a caption to make your solution more usable.

Simple Set Example

In this example, we are going to pick a list of college level Education attribute members from the Adventure Works sample cube. Education is an attribute hierarchy that is part of the Customer dimension. Here is the MDX for that set:

{[Customer].[Education].&[Bachelors], [Customer].[Education].&[Graduate Degree]}

Here is how I used that in Excel with the CUBESET function (AdvWorks is my connection name).

=CUBESET(“AdvWorks”,”{[Customer].[Education].&[Bachelors], [Customer].[Education].&[Graduate Degree]}”,”Completed College”)

While this is a simple example, any MDX set will work in the expression. If you need to create a set dynamically such as a Trailing 12 Months or Top 10 set it will work just as well. Work out the set in SQL Server Management Studio and then put it into a cell and refer to that cell when creating your cube value.


The CUBESETCOUNT function can be used to count the members in a set returned by a a CUBESET function. In MDX we use .count or COUNT() to determine the number of members in a set. This does not work with the CUBESET function and thus we have CUBESETCOUNT. This is a fairly simple function to use, but it is very powerful if you are trying to do dynamic set counts based on reference data on your spreadsheet.

Counting a Set of Customers with Sales for the Selected Period

In this example, we have created a set which returns customers with orders in 2011. We will count this set using the CUBESETCOUNT function to determine the count. In Excel, we could use the NOW() function to get the current year or some other dynamic value to build the set. However, Adventure Works is a static set so I am using a single year in the example.

nonempty( {([Customer].[Customer].[Customer],[Measures].[Internet Order Quantity])},[Date].[Calendar].[Calendar Year].&[2010])

This can be put into a CUBESET function as follows:

=CUBESET(“AdvWorks”,”nonempty( {([Customer].[Customer].[Customer],[Measures].[Internet Order Quantity])},[Date].[Calendar].[Calendar Year].&[2010])”)

Next, we put the CUBESET function into the CUBESETCOUNT function.

=CUBESETCOUNT( CUBESET(“AdvWorks”,”nonempty( {([Customer].[Customer].[Customer],[Measures].[Internet Order Quantity])},[Date].[Calendar].[Calendar Year].&[2010])”))

This can now be used as a value for other calculations. For example, you could show the average sale amount for customers who purchased something this year or even the average purchase amount this year for those who ordered last year to see if your repeat customers are buying more.

Wrap Up

Using these functions with other CUBE functions increases the flexibility of your dashboard solution and allows you to make many more creative visualizations. Remember to use captions with CUBESET functions you plan to use in your formulas and you need a CUBESET result to count with CUBESETCOUNT.