GigaOm highlights some emerging trends in new big data systems starting to make use of machine learning to actually get smarter as more data is ingested.
Normally lists are the top 5 best, but here’s a post from GigaOm with a list of 5 low-profile startups that could change big data.
Here are the videos from the Giga Om Big Data Conference that just concluded in New York. One of the talks featured Greenplum founder Luke Lonergan. And here’s another talking about Open Source’s role in big data.
I’m interested to hear how this conference compared to the O’Reilly Strata Conference.
GigaOm is putting on the Structure Big Data Conference next week in New York. Check out the schedule, lineup of speakers, and their list of 5 reasons to attend.
IBM and Revolution Analytics have integrated R with Netezza. Check out the GigaOm recap.
As the Open Source software movement continues the strengthen, questions abound about where the opportunities to create commercially viable solutions. Red Hat did it with Linux. Can Cloudera do it with Hadoop? Read this GigaOm article.
In an effort to increase user engagement, satisfaction, and profitability, many websites are offering their users various types of recommendations. Many people are familiar with Amazon.com’s people who bought also bought or people who browsed also browsed. But how do they do that?
Darren Vengroff, chief scientist from RichRelevance, explains some of the components of a recommendation system in a GigaOM article.
GigaOM posted an article claiming that we are in the midst of a data mining renaissance. Sounds good to me.

