February 27, 2012
The buzz around big data is driving further interest in the entire analytics market. Applying analytics to big data is the driver behind creating new, game-changing business value for enterprises. New analytic techniques and tools are being introduced into the enterprise to help spur on the big data analytic challenges. At a market buzz level, many of these tools and approaches appear equivalent, but when you start to look into the details there are distinct benefits, both today and with the direction these tools are taking in the future, that will constrain your big data analytic capabilities.
February 21, 2012
Gartner has published their latest iteration of the Data Warehousing DBMS Magic Quadrant (MQ) – a report in which IBM has been in the Leader quadrant since the very first MQ issued in June 2001.
February 13, 2012
In my previous post, I defined a framework by which to evaluate the appliance claims of data warehouse and analytic vendors. These truisms, which I have come to refer to as the golden rules of appliances are:
February 8, 2012
I was speaking at a conference last week (Heliview BI, in Holland) and my theme, as is pretty usual now, was the place of the data warehouse in a big data strategy. I had a packed room, but I suspect, it was the title not my reputation that filled it. It went well, as it usually does. I think that’s because I pitch it from the business benefit angle and spend more time on the use cases, than the technology.
February 6, 2012
The term "appliance" is liberally used by many vendors in the big data space these days. It seems that almost everyone has latched onto the term and it is being used not only to define data warehousing and analytic product offerings, but also to subtly (or not so subtly in some cases) set customer expectations about the underlying ease of deployment and ongoing cost of ownership associated with the product.
February 3, 2012
These days, it’s hard to find a business conference or read a publication that doesn’t talk about big data. Even the recent World Economic Forum in Davos, Switzerland, featured more than 40 presentations on this hot technology. Because of all the recent talk, many people think big data is new. While it’s true that big data is suddenly gaining more attention, we at IBM have been investing in this space for many years, and are confident that we have the strongest strategy and deepest solution offering on the market. Now, an independent research firm has validated our belief.
February 3, 2012
A number of Teradata customers have moved some or all of their data and analytic applications to IBM Netezza data warehouse appliances. The reasons these customers give for their move invariably include: Time to value Agility and the ability to grow with new workloads Reducing their cost of ongoing maintenance Improving query performance – particularly for complex analytics and ad-hoc environments as data volumes grow.
January 26, 2012
Is 2012 the year of Agile Analytics? Recent publications show growing interest in the application of Agile methods to analytics: Ken Collier, an Agile pioneer, tackles analytics in his aptly named new book Agile Analytics. A quick Google search surfaces a number of recent blogs and articles. Curt Monash recently published an excellent two-part blog on the subject.
January 24, 2012
In talking to customers, analysts and partners at the National Retail Federation “Big Show” last week, it was clear to me that retailers are trying to find the “holy grail” in the cross-channel retailing environment that offers “one view of the customer across all channels.” Power has shifted to consumers as shoppers use multiple devices to price-compare and use the store as a place that offers them convenience, instant access and price efficiency, but not much more. Loyalty seems to be a thing of the past.
January 13, 2012
Still NOT Positioned For Analytics Oracle’s Big Data Appliance, originally announced in October 2011, is now officially for sale and includes the Cloudera distribution of Hadoop. Despite the inclusion of Cloudera, Oracle's position on Hadoop remains fundamentally different than IBM. IBM embraces Hadoop for all use cases, especially as a platform for analytics. Oracle continues to position Hadoop and their Big Data Appliance strictly as a platform to acquire and transform unstructured data to be loaded into Oracle database for analysis.