James Kobielus recaps the quick-hit ponderings from the IBM Netezza Facebook page. He went deeper on the themes of sexy statistics, Hadoop uber-alles, smartphones as big data analytics platforms, and big data's optimal deployment model. And he opened up a fresh topic: frictionless sandboxes.
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
Here are the quick-hit ponderings that I posted on the IBM Netezza Facebook page this past week. I went deeper on the themes of experience optimization, Hadoop, big data crowdsourcing, and DW appliance proofs of concept. And I opened up a fresh topic: big data's optimal deployment role. I also
Here are the quick-hit ponderings that I posted on the IBM Netezza Facebook page this past week. I went deeper on machine learning, continued my meditation on all-in-memory, put out some more Hadoop thoughts in advance of next week's Hadoop Summit (where IBM's Anjul Bhambhri will speak on
The biggest table in any Netezza database that I know of has over 600 billion rows!! That’s the claim made by our customer, Catalina Marketing.
So although most of the data in the world is not relational, there is a huge amount of relational data and IBM technologies are more than capable of