Happy 150th Ft. Myer, VA

From 1989 to 1992 I had the unique experience of being in the oldest infantry regiment in the US Army – The 3d US Infantry (The Old Guard).  Our headquarters, located at Ft. Myer in northern Virginia, was and continues to be the site of significant historical events.  I was located just across the river at Ft. Leslie J. McNair in southwest Washington, DC and spent a great deal of time at Myer due in part to the HQ connection but also because Myer is immediately adjacent to the premier memorial to our Nation’s conflicts – Arlington National Cemetery.  Today, 5 June, 2013 is the 150th birthday of the defensive outpost known originally as Ft. Whipple.  I appreciate the place Ft. Myer has had in our history and the supreme honor and discipline embodied in the professional soldiers there, past and present.

For deeper treatment of the topic see Mr. John Michael’s well-researched blog and associated book:  http://www.historic-fortmyer.com/2013/06/05/happy-birthday-fort-myer-defending-the-capital-for-150-years/

Meetup for Tampa Analytics Professionals

I’ve started a meetup for local professionals in the decision science field around the Tampa Bay area to come together and learn about what’s happening in our area.  If you are a data science professional, come join us and be a part of making the Tampa-St. Petersburg metro area the southeast center of excellence in big data and analytics.  Visit http://www.meetup.com/Analytics-Professionals-of-Tampa/ to find events and to join.  I hope to see you there.

US Government Business Capture Data Mining in Microsoft Excel

View agency activity clustering on geography in Excel using Excel Data Mining Add-ins

By Don Krapohl

1.       Ensure you have downloaded the Excel Data Mining Add-ins from Microsoft at http://www.microsoft.com/en-us/download/details.aspx?id=35578 .  The article assumes you have a working version of the DM Addins and a default Analysis Services (SSAS) instance defined.  Search for getting started with SQL Server Data Mining Add-ins for Excel if you are not familiar with this process.

2.       Open the Excel sample file for Federal contract acquisitions in Wyoming (2012) from http://www.augmentedintel.com/content/datasets/government_contracts_data_mining_addins.xlsx

3.       On the wy_data_feed tab, select all the data.

4.       In the Home tab on the ribbon in the Styles section select “Format as Table”.  Pick any format you wish.

5.       A new tab will appear on the ribbon for Table Tools with menus for Analyze and Design as below.

Microsoft Excel Table Tools menu
Table tools to format data as a table in Excel


6.       On the Analyze menu, select “Detect Categories”.  This is will group (cluster) your information on common attributes, particular commonalities that are not obvious or immediately observable.

7.       Deselect all checkboxes except the following:

a.       Dollars Obligated

b.      Award Type

c.       Contract Pricing

d.      Funding Agency

e.      Product Or Service Code

f.        Category

8.       Click ‘run’

9.       The output will show you categories of information showing strong affinities.  Explore the model by filtering the charts and tables by the category/ies generated.  Do this by selecting the filter icon (funnel) next to Category on the table or the Category label at the lower left of the graph.

10.   Interesting information may be derived from the groups with fewer rows that may show particularly interesting correlations for a targeted campaign.  For example, filter the table and chart on Category 6.  This group indicates a group affinity for the attribute values ProductOrServiceCode = “REFRIGERATION AND AIR CONDITIONING COMPONENTS”, fundingAgency = “Veterans Affairs, Department Of”, and a contract award value of $61,148 to $1,173,695 as shown below:


Importance of data categories in Excel Data Mining Add-ins
Factor Analysis in Microsoft Excel

For my organization’s business development activities, if I am in the heating and air business I may elect to focus efforts on medium-sized contracts with Veterans Affairs.

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