Going, going...gone! That phrase has been used by auctioneers to indicate the final bid opportunity for a hot auction item. Now “going, going, gone” is being used in the world of big data. Why? Organizations realize that they need to act faster by analyzing streaming data and taking action in the
IBM has a long and successful history with open source, from running Linux on IBM PCs to contributing initial codebase for Eclipse. We believe a mix of open source and closed source is the best way to drive adoption in the marketplace. Having the full support of a vendor like IBM can lower risk
If you take a quick glance at any technology publication (and many business publications as well) you will likely see some reference to real-time. There’s real-time customer service, real-time marketing, real-time analytics and the list goes on. But what does real time mean? Is there a standard
Industry analysts project that 30% of companies will “monetize their data” by 2016. But what does this mean? Many organizations are trying to figure out how to turn their data into a gold mine. The reality is each business is unique and data monetization projects should be customized to focus on a
Roger Rea, product manager of InfoSphere Streams, explains what stream computing is, how it differs from event processing and CEP and gives examples of how companies are employing stream computing for real-time analyses and applications.
What is “event processing”? What are the similarities and differences between complex event processing and stream computing? Why would you want to use these techniques? Roger Rea, IBM InfoSphere Streams product manager, answers these questions and others.