advanced analytics
Workload-optimized Systems? Scale In, Out and Up for Balanced Big Data Configurations
October 2, 2012
Big data is, fundamentally, a cloud-computing approach to advanced analytics and data management. The images that come to mind when somebody says “cloud computing” are a) increasingly sprawling server farms and b) increasingly huge server racks arranged in endless rows within these farms. Read More
Top Reads in Big Data: Week of Sept. 9
September 14, 2012
"Value" is the key word in several of my top picks this week. From saving money to saving lives to saving time in who you follow on Twitter, we're still finding new ways to get value from data. Read More
Next Best Action: Its Leading Synonyms and Trailing Cynicisms
August 22, 2012
"Next best action” is a hot focus area under big data, advanced analytics, digital marketing, smarter commerce and other business imperatives. Enterprises have been doing next best action, in various forms, for years. Read More
Data Scientists: Credentialed or Otherwise
August 13, 2012
For the past 2 months, a LinkedIn discussion group has been debating the burning question "Do You Need a PhD to Analyze B Read More
Welcome to The Big Data Hub
August 6, 2012
Have you wondered to yourself – or asked out loud – “What is big data?” Chances are pretty high you have, and if so, you are certainly far from being alone. Read More
Make Turing Proud: Next Best Action in Multichannel Conversations
June 26, 2012
By using your data, you can "humanize" your conversations with customers, regardless of which channel they use to interact with your organization. Find out how IBM Watson's architecture may serve as a model for more intelligent engagement.
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Response: Top 5 Myths about Big 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.
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Data Scientists: Run Your Mad Experiments
June 18, 2012
Smarter business is a game of incremental improvements. It depends on your ability to produce a steady stream of innovations in your operational processes.
Incremental tweaking is not usually a glamorous activity. Minute process adjustments don't usually call attention to themselves. And that's a good thing, because you can roll them out in stealth, with competitors not suspecting or customers detecting any disruptions in your quality of service.
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Data Scientists: Illuminate Your Patterns with Pictures
June 4, 2012
Scientific inquiry is all about finding non-obvious patterns in observational data. It's no surprise that that is also the core of data science. This post examines that phenomenon in data science.
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Week's Worth of Koby Quick-Hits May 16th to 18th 2012
May 23, 2012
Here are the quick-hit ponderings that I posted on the IBM Netezza Facebook page this past week. Clearly, I was focused on the "big" side of big data, and on the "statistics" DNA of the analytics that power big data, and on the limits of what you can in fact "optimize" with big data and analytics:
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