May 15, 2013
Although I live in Australia, work brings me to both the USA and Asia where discussing big data projects leaves me with the impression of significant differences in adoption rates and approaches between organizations in both regions.
May 14, 2013
The petroleum industry is no stranger to large volumes of data.
May 10, 2013
This week’s Friday Data Flick gives you insight into “operations analysis,” which is one of the top five uses (also called “use cases”) for big data. Operations analysis is about analyzing a variety of machine data to get improved business results.
February 28, 2013
When talking about big data, the terms "structured" and "unstructured" often arise. Data scientists must boldly break out of the structured data world to consider not only unstructured data, but also unstructured processes and governance, and collaboration models in big data applications.
November 1, 2012
The need to innovate and stay ahead of customer demands is even more imperative today.
August 21, 2012
Recently, I was in Nice for a three-day gathering of 150 European IBM Big Data specialists. Looking around the room at the opening plenary made me think how fast the world of big data is moving and how quickly our community is growing.
August 16, 2012
Among healthcare executives interviewed for the 2010 IBM Global CEO study, 90% expect a high or very high level of complexity of data over the next five years, but more than 40% are unprepared to deal with it.
August 11, 2012
For some vendors, the only use case for unstructured data is to turn it into structured data to analyze it in a relational database.
June 26, 2012
What exactly is 'semi-structured' data? How is it different from relational data? And what about 'structured, but not relational' data? Dai Clegg explains the intricacies of semi-structured data and how it fits into relaitonal or Hadoop platforms. Using an example of a telco seeking affinity analysis, find out how to leverage semi-structured data.
June 21, 2012
Jim Kobielus responds to a Mashable post by Brian Gentile on the "Top 5 Myths about Big Data." He offers some additional thoughts on volume, Hadoop, unstructured data, sentiment analysis and NoSQL.