I was talking to one of the prominent General Partners at a Venture Capital
Category: Data & Analytics
Data becomes so complex that it is nearly impossible to work with existing data infrastructure and analysis techniques. My suite of data technology includes: 1) Real-Time Stream Processing (providing in-memory analytics, ETL, and CEP); 2) Ad-Hoc NoSQL Query (providing interactive fine-grained analytics); and 3) Batch Processing (providing off-line analytics over large volumes). Talk to me about he world of SQL vs. NoSQL, proprietary vs. open source.
My experience in analytics started when I spearheaded a data mining workbench at Teradata in 1996 that included machine learning algorithms including rule induction, decision tree, kohonen clustering, deep learning neural networks, and a host of others. I’ve been a student of ML and AI since 1988, and using it across large datasets over two decades before it became a huge focus of innovation.
There is an important dimension in the Big Data space….the dimension of time, that few
Big Data is confusing to most executives. It’s this nebulous concept of applying technologies from
I was touring what reminded me of the Cheyenne Mountain nuclear bunker – one of
Now that the chimps have welcomed me in, I’m quickly feeling the change begin. Not
Do you think they truly under stood just how fast the data infrastructure marketplace was
Is Big Data destined for only the top 3,000 companies worldwide? What about medium or
Traditional Analytics Approach The front-end of the above analytics architecture remains relatively unchanged for casual
Enhancing the multichannel consumer experience should be the focus of all retailers (especially brick and
Shouldn’t data structures be declared at query time, not at data load time? Or some