@philsimon on what to expect in 2013 for data management.
Tag: hadoop
@philsimon on innovation from a very unlikely source.
@philsimon on some Big Data characteristics.
David Linthicum wrote a blog post entitled "3 winners, 3 losers in the move to big data" on InfoWorld and notes that traditional vendors "did not see this coming" (big data that is). Since David made some interesting points, some of which I agree with, some I disagree, I felt it worthwhile
Well, it's certainly a provocative title, and hopefully it will be a thought provoking conversation. I am participating in a panel discussion along with Philip Russom of TDWI, David Menninger of EMC, and James Markarian of Informatica. The discussion will be hosted by DM Radio hosts Eric Kavanagh and Jim Ericson. The interview occurs
In my previous two posts I introduced the need for data quality and big data and discussed the need for fit for purpose data quality and for stretching the limits of data quality for big data. In this final post on data quality and big data I’ll address the following:
Hadoop – it’s not just hype! The community has shown tremendous interest in our plans for Hadoop – what will be supported, when it will be available, and so on. We’ve been blogging about big data and provided early plans for Hadoop, including SAS/ACCESS support for Hadoop. Well, it's official:
Mike Ames and I recently had an opportunity to talk to Fern Halper and Judith Herwitz from Hurwitz & Associates as they are doing a 4 part blog series on vendor views on big data and big data analytics. You can view Fern's blog post about the SAS perspective here. Here
It’s hard to believe, but now that 2011 is almost over it’s time to look ahead. The technology pundits are starting to publish their 2012 predictions, and it’s not surprising to see topics like analytics, cloud, big data, mobile, social networking, virtualization, open source on these lists. Instead of creating
Big hype about big data has played a significant role in driving awareness about the value of analytics. SAS welcomes the interest in big data, since it highlights our ability to work with huge volumes of complex and diverse data. Since this is such a critical topic, we have formulated