AUG 23, 2012 8:57am ET

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Big Data Exploration and Experimentation for Business Insight and Innovation


In the book, “The Singularity is Near,” author Raymond Kurzweil envisions a future where information technology advances so far that it allows the human race to break the barriers of our biological limitations.

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Comments (2)
The advancing of hardware architecture - such as 64-bit platforms becoming common, server clustering, et. al. - facilitates use of disruptive technologies such as QlikView from QlikTech for both data and business discovery. Instead of using a timeworn approach that essentially requires knowledge of the answer before the question is asked, business/data discovery allows analysts and others throughout the enterprise the capability to be creative - rather than simply a consumer/reviewer of canned reports supplied by I/T. This, of course, aligns with your perspective of quickly identifying what does and does not work and add value - beyond 'fast fail' to 'fast success.'
Posted by Gary B | Thursday, August 23 2012 at 11:28AM ET
The lack of exploration and experimentation for insight and innovation, as you point out, are due to the time and cost involved. However, this is not just for big data projects but, I believe, also for smaller data volumes.

What are available to support this experimentation are methodology recommendations (agile development, for example) but no technology. The technology support is at best in the self-service BI world and this is a far simpler world that the one you are talking about. We need technology that will enable people to not only "take a business problem or thesis and work with small, well-defined data sets, model, integrate, analyze and examine the results of the experiment; understand what worked and what didn't, refine the process and repeat" but also do so faster, while dealing with large volumes of data and 100s of diverse data sources. And faster the better, at least 2-3x, over what can done today.

Achieving this means technology that offers: a simplified DI/BI/analytics stack so component integration, meta data management, and keeping components in synch can be simplified, and hand-offs eliminated; a schema-less DBMS so data integration is easier; a columnar DBMS so that queries and analysis execute 10-100x faster; and a programming approach that reduces development time by 2-3x.

QIM Analytics provides a data integration and analytics middleware platform that meets the above requirements - enabling data exploration and experimentation to generate insights and innovation at least 2x faster than current technology on Bs of rows, 10s of TBs, and 100s of sources.

Ram Udupa QIM Analytics

Posted by Ram U | Friday, August 24 2012 at 4:08PM ET
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