DEC 5, 2012 8:37am ET

Related Links

Health Information Exchange Requires Nationwide Patient Data Matching Strategy
August 14, 2014
Analytics CEO Schools Payers at AHIP
June 16, 2014
Making Sound Business Decisions
June 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

The Future of Data Wisdom


I recently finished reading the TED Book by Jim Hornthal, “A Haystack Full of Needles,” which included an overview of the different predictive approaches taken by one of the most common forms of data-driven decision making in the era of big data, namely, the recommendation engines increasingly provided by websites, social networks, and mobile apps.

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 information-management.com 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 (2)
Excellent piece Jim. I think that, as you describe, the wisdom of crowds, friednds and experts will converge (eventually). I also think that in order for this to happen and be most effective, there must be a recognition that correlations need to be combined with causality. Right now, I don't feel that machine learning has progressed to the point where causality can be determined in a consistent way which means that we'll always have to rely on those pesky humans to make sense of it all.
Posted by Mike W | Wednesday, December 12 2012 at 4:56PM ET
Thanks for your comment, Mike.

The intersection of crowds, friends, and experts will certainly generate a lot of correlations, many of which will provide little to no predictive value. Causality often alludes both computers and humans. Data-driven decision making will require combining all potential signals while needing all the help it can get to filter out the noise. Sometimes that help will come more from the computers, and other times that help will come more from the humans, but as you noted, both machine and man have to be involved in the learning process.

Best Regards,


Posted by Jim H | Wednesday, December 12 2012 at 7:58PM 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.