I recently attended the Cloud Expo in New York City where big data was a key topic. Keeping with the various topics addressed at the event, here are my thoughts as they relate to the Cloud Expo. Warning: if you are searching for strong conclusions or straightforward advice, you’ll need
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
In my last post I set the stage for data quality considerations for big data. Today, I’ll cover the following big data and data quality considerations: Data quality efforts should be "fit for purpose" Extend data quality by thinking “outside the box” Data quality efforts should be "fit for purpose"
Marketing is a big part of my job so I should be supportive of efforts to capitalize on the trend of the day. But given my background in R&D, I am dubious of marketing efforts that are not backed up by real product or solution capabilities. So, I’m a bit
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:
I recently presented a session on big data at the 13th Annual Privacy and Security hosted by the Province of British Columbia and held in Victoria. There were a number of interesting discussions and presentations that relate to privacy and security ramifications of big data. The discussion was timely given
I participated in a lively TweetJam discussion sponsored by Gartner last Friday. In addition to learning that the iPhone twitter app is not the easiest way to read and tweet quickly, there were a number of interesting observations shared by the participants, along with a good bit of humor. We
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
