Tam, good article. One solution that can help turn bigdata problems into big opportunities for any industryis HPCC Systems from LexisNexis which provides for an efficient low cost one-stop solution for BI and analytics needs. This open source enterprise-ready solution is comprised of a single platform that is easy to install, manage and code. Their built-in analytics libraries for Machine Learning and integration with other open source tools like Pentaho provide companies with an end to end solution for ETL,data mining and reporting. For more info visit: hpccsystems.com
@WB: Well, this is an additional perspective of the matter; as far as I know, it is a technology still really expensive a it is still strong trying to bring it on the ground for public use, respect to current legacy memories adopted. Maybe it will be good in the future, once again, not so easy (in my modest opinion), trying to define a credibile horizon for its definitely adoption.
The growing trend for that, i would say unstructured data - the adopting scheme for data distribution a major contributing factor. How many internet firms out there are handling unstructured data well? I dont know the impact of machine learning technique employing by Facebook, Amazon and Google etc in reducing the complexity. According to a report, put an estimate monthly internet data flow at near 21 exabytes of data, that's massive, i think. And we just have to prepare for more explosion of data few years time. A huge task?
The believe at many companies is that they need more data, about customers, the economy, suppliers, end markets, etc. Yet most haven't figured out what to do with the data they currently have.
@FlyingScot, which company do you work for? There are some big names that are working on smarter ways to analyze the data as the amount of data is growing per day and the cost associated with storing and analyzing is huge. But there are rich dividends in these fields.
@Wale, you are correct that storing, accessing and using the data is huge task. The current methods of storing the data is really inefficient and we need new methods to store data. Researchers are working on ways to store data on elementary particles but if we can tap biological material to store the data then we can probably store data cheaply.
I think more challenging tasks still lie ahead - managing data across board big issue. Movement of data across - who's accessing what and what's being accessed? Nanotechnology would probably be taking care of more memory - nanoscaleability of memory device in particular very pertinent. Human genes?
Personally, I am feeling that on this matter, a strong point to address in the near future, will be about mobile data, in terms of how to store and provide secured features for allowing the online access.
Our company is not doing a lot on the big data front. I suppose it is a story of lots of data but not much information. Like many I suppose we need to do a much better job on this front.
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Join EBN contributor Jennifer Baljko on Thursday August 23, 2012, at 11:00 a.m. EST for a live chat on how electronic manufacturers in Thailand have shored up their supply chain to reduce the impact of future natural disasters.
Peter Drucker famously said "Trying to predict the future is like trying to drive down a country road at night with no lights while looking out the back window." Yet in the razor's-edge world of electronics—with a lean supply chain and just-in-time demands—the need to know the future is vital.
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