Is Big Data Just Data?

Richard Marshall at Decision and Data Sciences recently posted a blog entry based in part on conversations during the NIST Big Data Taxonomy and Definitions group meeting.  He brings up a few good points, especially that volume isn’t a new thing in data and velocity is a niche problem.  As initially stated by the chair, Nancy Grady of SAIC, variety of data may be the true litmus test and the factor that changes the management and analysis lifecycles.  Read his full blog at http://ddsciences.com/why-big-data-is-different/

Predicting the Best Parameters for Federal Business Capture using WEKA

Which contract parameters should I choose?

What combination of features might I pursue to raise my probability of contract award?

  1. Open WEKA explorer
  2. On pre-process tab find the government_contracts.arff file.
  3. Perform pre-processing
    1. Escape non-enclosure single- and double-quotes (\’, \”) if using a delimited text version.
    2. Check ‘UniqueTransactionID’ and click ‘Remove’.  Stating the obvious, there is no value in analysis of a continuous random transaction ID, discretization and local smoothing  can lead to overfitting, and it has no predictive value.
    3. If you have saved the arff back into a csv you will have to filter the ZIP code fields RecipientZipCode and PlaceOfPerformanceZipCode back to nominal with the unsupervised attribute filter StringToNominal and DollarsObligated to numeric.
    4. On the Associate tab, select the Apriori algorithm and click ‘start’.  The results:

 

WEKA association rules for contract feature prediction
Predicting Award Parameters

 

This indicates that selecting for Firm Fixed Price contracts for the VA, if you are located in ZIP 83110 and the work will be performed within ZIP 83110 you may have an advantage in the acquisition.

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Integrated Approach to Organizational Development

Organizational Development Through Distilled Best Practices

“Pain is temporary. Quitting lasts forever.”
― Lance Armstrong, Every Second Counts

Your small company is bulging at the seams on its way to mid-size stardom and needs structure to let you reach your next goal. Rapid organizational maturation, organizational development, or organizational transformation are difficult with the profit-driving aspects of the business mounting pressure on disconnected technical focus areas. Each knowledge area or domain, such as project management, software development, data analysis, reporting, systems administration, and service desk tier 2/3 may be performed by one or two individuals. To advance, the company must grow into specialization and with that comes the additional problems of aligning work across departments.

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