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«October 2015»

Data Warehouse from the Ground Up at SQL Saturday Orlando, FL on Oct. 10th

SQL Saturday #442SQL Saturday #442 is upon us and yours truly will be presenting in Orlando, Florida on October 10th alongside Mitchell Pearson (b|t). The session is scheduled at 10:35 AM and will last until 11:35 AM. I’m very excited to be presenting at SQL Saturday Orlando this year as it’ll be my first presenting this session in person and my first time speaking at SQL Saturday Orlando! If you haven’t registered yet for this event, you need to do that. This event will be top notch!

My session is called Designing a Data Warehouse from the Ground Up. What if you could approach any business process in your organization and quickly design an effective and optimal dimensional model using a standardized step-by-step method? In this session I’ll discuss the steps required to design a unified dimensional model that is optimized for reporting and follows widely accepted best practices. We’ll also discuss how the design of our dimensional model affects a SQL Server Analysis Services solution and how the choices we make during the data warehouse design phase can make or break our SSAS cubes. You may remember that I did this session a while back for Pragmatic Works via webinar. I’ll be doing the same session at SQL Saturday Orlando but on-prem! ;)

So get signed up for this event now! It’s only 11 days away!

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Create Date Dimension with Fiscal and Time

Here are three scripts that create and Date and Time Dimension and can add the fiscal columns too. First run the Dim Date script first to create the DimDate table. Make sure you change the start date and end date on the script to your preference. Then run the add Fiscal Dates scripts to add the fiscal columns. Make sure you alter the Fiscal script to set the date offset amount. The comments in the script will help you with this.

This zip file contains three SQL scripts.

Create Dim Date

Create Dim Time

Add Fiscal Dates

These will create a Date Dimension table and allow you to run the add fiscal script to add the fiscal columns if you desire. The Create Dim Time will create a time dimension with every second of the day for those that need actual time analysis of your data.

Make sure you set the start date and end date in the create dim date script. Set the dateoffset in the fiscal script.

Download the script here:


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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 valu

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Excel 2013 Inquire Add-in

  • 11 February 2013
  • Author: DevinKnight
  • Number of views: 10672

What is Inquire

The Inquire Add-in for Excel 2013 helps you analyze and review your workbooks for things like relationships, invalid formulas, and to compare .xlsx files for differences.  Let’s take some time to review how to enable the add-in and then how to use it.

Enabling the Add-in

If you are using Office Professional Plus, the Inquire add-in comes installed with Excel you simply need to enable it.

The Inquire add-in is already installed with Excel 2013 you simply need to enable it by going to File –> Options –> Add-Ins.  Then Select COM Add-ins from the Manage dropdown and click Go


Check off Inquire from the Add-Ins available list then click OK.


Once you have enabled the add-in the INQUIRE tab will appear in the increasingly crowded Office ribbon.


Let’s take a look at what this new add-in has given us.

What does it do?


Workbook Analysis

The Workbook Analysis tool is used for analyzing details of a workbook for reporting on the things like the workbook structure, formulas, cells, ranges, and warnings.


One odd thing here that a lot of people notice a workbook structure property called “Very hidden sheets”.  This is simple another way of hiding sheets through VBA.  See here for more details on how to do a Very hidden sheet.


Workbook Relationship

The Workbook Relationship tool shows links between multiple workbooks that you may have.  This can be especially helpful when you have dozens of cell references to an external workbook.  Trying to untangle that mess can be very difficult and this tool visualizes those dependencies.


Worksheet Relationship

The Worksheet Relationship tool works exactly the same as the Workbook Relationship but now visualizing dependencies at the sheet level.


Cell Relationship

Again the Cell Relationship tool is very similar but it only shows relationships of cells that you have highlighted prior to click on the command.  These are often dependencies are often displayed because a cell is referenced in a formula.



Compare Files

The Compare Files command lets you see the differences, cell by cell, between two workbooks. You need to have two workbooks open in Excel to run this command.

Any differences that the compare tool finds color coded by content type in a grid view.  Here’s an example output:



Clean Excess Cell Formatting

If you've developed an Excel workbook that’s gotten out hand with how large it is and how much logic is built in use the Clean Excess Cell Formatting tool to remove extra formatting on cells that you may not be aware of. 

This can actually help increase the performance and file size of workbook that have become bloated with this kind of leftover formatting.  You can test it out by putting a background color on a couple irrelevant cells and then run the tool.

Workbook Passwords

If you are using the Inquire add-in for analyzing workbooks that are password protected you must add the workbook password to the Password Manager.



This is the standard Excel Help that will walk you through what the add-in does.

I’ve found the Inquire add-in has a couple nice features that i can definitely see myself using in our increasingly Excel centric world we live in.

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