I covered this topic of simple queries over large data sets at a recent GigaOm conference, "Creating simple queries over huge data sets can provide insights much more quickly and with more accuracy than trying to create sophisticated algorithms narrowed toward smaller samples. The scene-completion process for Google's Street View (which removes offensive or embarrassing images and "fills in" the scene) went from using a complicated formula over about 150,000 photos to a simple formula, but with more than 1 million photos with vastly superior results, said (Jack Norris, vice president of marketing at MapR Technologies). The same process could apply to financial services, customer sentiment, weather forecasting or anywhere big data sets could be combined with a simple query process." This is a very different approach from traditional business analytics.
If you take big data analysis as a distinct category, SAS is in the middle of the pack. In an analysis of big data revenue for the Wikibon consulting site, analyst Jeff Kelly puts SAS' big data revenue at $187 million, just $1 million ahead of startup Splunk and far behind IBM.
While it is very difficult to break out big data (a somewhat amorphous term), the business intelligence world is changing. For example, the community developed and free statistical language R is the basis for new SAS competitors including Revolution Analytics. SAS has announced support for R, but that is a long way from basing your products on a new model.
The Amazon Web Services conference was being held a short walk from the SAS event. Amazon has its own open source demons to contend with (OpenStack is a clear competitor to AWS), but the transparency of AWS pricing, the continued price cuts paired with new features and the ability to ramp up or down infrastructure services as needed do point to the new way to acquire enterprise computing services.
SAS seems intent on providing its software as a cloud service, but whether it will be willing to adopt the high volume, low price economics of an Amazon is a different case altogether. Amazon's retail operations are powered by some of the most sophisticated business intelligence operations in the world. Those customer-facing business intelligence capabilities brought to the market place at an Amazon-like pricing model may indeed be the future of the intelligent business model for the likes of SAS and its competitors.
Eric Lundquist is a technology analyst at Ziff Brothers Investments, a private investment firm. Lundquist, who was editor-in-chief at eWEEK (previously PC WEEK) from 1996-2008 authored this article for eWEEK to share his thoughts on technology, products and services. No investment advice is offered in this blog. All duties are disclaimed. Lundquist works separately for a private investment firm which may at any time invest in companies whose products are discussed in this article and no disclosure of securities transactions will be made.