IBMs Info On Demand Gig Gears Up to Ease IT Pain
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Q&A: Steve Mills, of IBM's Software Group, discusses how IBM plans to fix the problem of quickly serving up relevant information building up in growing data stores.
Charles Garry says that IBM needs to act boldly in the database field. Click here to read more.
You have squad cars with wireless connections. Theyre requesting information, having to sift through large numbers of records, often millions of records, sifting through information that gives you probable matches to people who might be associated with a crime. That kind of real-time crime fighting wasnt possible years ago. The bandwidth and the software sophistication wasnt [available] years ago.
In a panel presentation, Scott Vanderhoef, county executive of New York State Departments Rockland County, also talked about setting up, with IBM, Verify NY, a new county-specific data-mining computer system to weed out fraud in the states Medicaid program. What are some of the examples of noise—irrelevant data—you have to deal with in that scenario?
[With the Medicaid project], the tough part is trying to figure out if a problem was from a [healthcare] provider or an individual citizen. The problem might seem like theyre overclaiming, or double submitting.
Given IBMs investments, both in acquisitions and in todays announcement, the company must see this as a huge opportunity.
Weve been investing quite heavily over the last five years in getting access to data in all forms, in all places. How do you bring it together? How do you apply sophisticated algorithms to information?
Theres a big business opportunity associated with this. Because technology and know-how have come together to allow us to do things we couldnt do years ago.
The $1 billion investment on software, the 15,000 [IBM experts] on the service side, with another 10,000 [personnel] coming, the reason for that is we in fact see these things coming together. The need is there. Weve been building know-how in different domains.
Whether its government entitlement programs, discovery in various industry segments, healthcare getting a huge amount of attention, common healthcare records—being able to do manipulation for outcome-related treatments so you understand what different therapies will result in, so you can compare data, so you can understand what to prescribe for someone. All this will be information-based. It will be huge amounts of information to be correlated, related, manipulated.
The next wave of innovation is going to come through various aspects of information understanding, manipulation and decision making, in real time.
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