Entries Tagged as 'Add-ins'

Video Tutorials for Business Intelligence with Excel 2007

MyVBProf.com hosts a set of great video tutorials for performing business intelligence tasks with Excel 2007. Bill Burrows starts with the installation of pre-requisites. He even shows how to make sure that Excel .Net Programmability Support is available! Wow!!

Bill then follows up with a set of tutorials on pivot tables and wraps up with videos on using the Table Analysis Tools from the SQL Server Data Mining add-ins for Excel. His approach is accessible, his style is captivating, his examples are meaningful and very well explained.


1. If you have SQL Server 2005 or 2008 CTP these tutorials give you a great start for BI using Excel and Analysis Service.

2. If you do not have SQL Server, get a free evaluation from http://www.microsoft.com/sql/downloads/trial-software.mspx, then go back to the previous point

3. You don’t have SQL Server, don’t want to try it out, don’t care about the data mining part — fine, just watch some of the tutorials to see what you miss!

Excel data mining cell functions

 In the previous post I presented a not-so-documented cell function installed in Excel by the data mining add-ins. Jamie also gave some cool demos featuring these functions. To complete this topic, here is a full description of the cell functions and how they can be used.

The Excel Data Mining Client add-in  includes 3 cell functions: DMPREDICT, DMPREDICTTABLEROW and DMCONTENTQUERY. These functions are included in the add-ins for SQL Server 2005, but not documented or supported. However, they will be both documented and supported in the add-ins for SQL Server 2008. 

To use these functions, you will need a mining model available on the server. For the examples below, I created a Microsoft Decision Trees mining model, built by running the Classify task in the DM Client add-in over the sample Table Analysis Tools Sample spreadsheet in the sample workbook installed by the  add-ins.

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Regression accuracy: Excel’s regression vs. the SSDM algorithm

A recent post on the MSDN Forums raised an interesting issue: Excel Data Analysis’s Linear Regression and SSDM were returning different results. Specifically, the SSDM results were much worse.

The issue turned out to be a data modeling issue (columns were not mapped properly).  However, during the investigation I had to compare Excel’s linear regression with the SSDM regression algorithm(s). Thought this might be interesting, so here is one way to compare the results from the two implementations.

I started with some simple (X,Y) data (available for download as a CSV file). First step - run Excel’s Data Analysis regression tool. The results are displayed typically in a separate spreadsheet, and the interesting part  is the Coefficients sections:


Therefore, the Excel regression formula is
Y = 2.37486095661847*X -0.310344827586214

Next thing — apply Excel’s regression coefficients to the existing data. I did this by adding a column in my data spreadsheet and populating it with a formula:

Next thing, I created a Microsoft Linear Regression mining model on the same data. There is a variety of ways to do this, such as exporting data to a table, connecting directly to the Excel spreadsheet or, the simplest way, by using the Excel add-ins.

To get the model’s predictions in Excel, I used one of the functions exposed by the Excel add-ins, DMPREDICT. If you do not have the add-ins you can always execute a prediction query in SQL Server Management Studio or BI Dev Studio.
However, with the add-ins’s function, getting the prediction results is really easy:

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