Missing the Ocean for the Stream: What We Can and Cannot Learn from IBM’s New Breakthrough
Christian Bonilla | July 7th, 2009Filed under: Managers View, Tech Trends | Tags: BI, business analytics, business intelligence, decision process, decision support, forward looking analysis, IBM, IBM System S, itemset detection, link detection, making better business decisions, predict the highest price at which a customer would be willing to buy a product, predicting the effect an advertisement will have in a market, predictive analytics, stream computing | 2 Comments »
As part of its perpetual quest to reinvent and perfect its business model, IBM has made an aggressive push into the analytics market in the last half-dozen or so years. The company’s slick, though occasionally confusing ad campaigns (remember those ads with the mysterious red box being unveiled?) often announce its new initiatives, though it is not always clear that a new announcement is indeed a major one. In the analytics space, however, Big Blue does mean business. The announcement of its sizable new business analytics and optimization division is clearly intended to prove as much. Shortly after its announcement, IBM also unveiled a new stream computing platform called “System S” to much fanfare. The breathless enthusiasm of business journalists, technology bloggers and investment analysts has been palpable. But what exactly does this technological advancement do, and what does it mean for your business?
To answer this question, let’s begin briefly by dissecting what IBM has introduced. Imagine that you are receiving a continuous stream of data, such as stock prices on the Nasdaq. These figures must be quickly analyzed so that the proper buy and sell orders can be placed. Suppose that you also need to base your decisions not just on the Nasdaq prices but also the numbers figures coming in from dozens of other exchanges. Read the rest of this entry »