Agencies See Big Data As Cure For Healthcare Ills - InformationWeek

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Agencies See Big Data As Cure For Healthcare Ills
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WKash
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WKash,
User Rank: Author
3/26/2014 | 3:10:38 PM
Federal government and Health Big Data
Federal agencies have been analyzing big pools of data for years. What's different today are the tools that make it easier for rank and file managers to access and analyze data that's relevant to them; and the ability to analyze data in real time, more or less. That said, the gap between promise and utility remains wide.  However, given the scale of what the VA does, and the NIH does in medical research, it makes sense that feds need to and can do more in pushing the big data envelope to improve healthcare. 
asksqn
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asksqn,
User Rank: Ninja
3/27/2014 | 2:51:56 PM
What happened to security?
No word, however, in La La land, as to securing these pie-in-the-sky Big Data plans.
HM
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HM,
User Rank: Moderator
3/27/2014 | 3:56:01 PM
Big Data Solution
Elena, very nice perspective on Big Data. We are seeing an increase in businesses seeking specialized skills to help address challenges that arose with the era of big data. The HPCC Systems platform from LexisNexis helps to fill this gap by allowing data analysts themselves to own the complete data lifecycle. Designed by data scientists, ECL is a declarative programming language used to express data algorithms across the entire HPCC platform. Their built-in analytics libraries for Machine Learning and BI integration provide a complete integrated solution from data ingestion and data processing to data delivery. HPCC Systems provides proven solutions to handle what are now called Big Data problems, and have been doing so for more than a decade. More at http://hpccsystems.com
Alison_Diana
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Alison_Diana,
User Rank: Author
3/31/2014 | 11:37:56 AM
Putting Information in the Right Hands
The most important element, as some have already said, is making sure regular users -- whether they're physicians, researchers, nurses, or accountants -- can access and use big data to do the analysis they want to do when and how they want to do it. It's critical to remove data scientists from the entire equation (yes, there's a role for them in super-complex scenarios, but not here). We all know how much easier and more satisfying it is to do a task ourselves. It also leads to more meaningful results and additional layers of usable information becoming available in a timelier fashion. 

Giving users control over this data frees up IT to focus on what they want and need to do, as well. 


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