Open Thoughts on Analytics
OCT 25, 2012 11:22am ET

Related Links

Business Analytics Services Spending to Reach $89.6 billion in 2018
September 15, 2014
Artificial Intelligence Meets the C-suite
September 15, 2014
Mayo Clinic to Use Watson to Bolster Trial Enrollments
September 11, 2014

Web Seminars

Essential Guide to Using Data Virtualization for Big Data Analytics
September 24, 2014
Integrating Relational Database Data with NoSQL Database Data
October 23, 2014

U.S. Baby Names: an Analytic Approach


I quite enjoyed the recent O’Reilly Webcast “Python for Data Analysis” by Wes McKinney. Besides learning about the useful Python shell, IPython, I was introduced to the powerful package pandas, which sits on top of NumPy and matplotlib, adding a wealth of easily-accessible “munging” and data analysis capabilities for Python programmers. McKinney was an excellent presenter, and I can’t wait to get his book this week at Strata + Hadoop World Conference in New York City.

Get access to this article and thousands more...

All Information Management articles are archived after 7 days. REGISTER NOW for unlimited access to all recently archived articles, as well as thousands of searchable stories. Registered Members also gain access to:

  • Full access to including all searchable archived content
  • Exclusive E-Newsletters delivering the latest headlines to your inbox
  • Access to White Papers, Web Seminars, and Blog Discussions
  • Discounts to upcoming conferences & events
  • Uninterrupted access to all sponsored content, and MORE!

Already Registered?


Comments (1)
Steve, good article. One other open source technology to look at is HPCC Systems from LexisNexis, a data-intensive supercomputing platform for processing and solving big data analytical problems. Their open source Machine Learning Library and Matrix processing algorithms assist data scientists and developers with business intelligence and predictive analytics. Its integration with Hadoop, R and Pentaho extends further capabilities providing a complete solution for data ingestion, processing and delivery. In fact, executing HPCC Systems commands within R helps ease the burden of memory limitations with just R alone. More at
Posted by HAANA M | Thursday, November 01 2012 at 9:45AM ET
Add Your Comments:
You must be registered to post a comment.
Not Registered?
You must be registered to post a comment. Click here to register.
Already registered? Log in here
Please note you must now log in with your email address and password.
Login  |  My Account  |  White Papers  |  Web Seminars  |  Events |  Newsletters |  eBooks
Please note you must now log in with your email address and password.