Last week I attended the IBM Big Data at the Speed of Business event at IBM’s Research facility in Almaden. At this analyst event IBM announced multiple capabilities around its big data initiative including its new BLU Acceleration and IBM PureData System for Hadoop. Additionally, new versions of Infosphere Big Insights and Infosphere Streams (for data streams) were announced as enhancements to IBM’s Big Data Platform. A new version of Informix that includes time series acceleration was also announced.
The overall goal of these products is to make big data more consumable –i.e. to make it simple to manage and analyze big data. For example, IBM PureData System for Hadoop is basically Hadoop as an appliance, making it easier to stand up and deploy. Executives at the event said that a recent customer had gotten its PureData System “loading and interrogating data 89 minutes.” The solution comes packaged with analytics and visualization technology too. BLU Acceleration combines a number of technologies including dynamic in-memory processing and active compression to make it 8-25x faster for reporting and analytics.
For me, some of the most interesting presentations focused on big data analytics. These included emerging patterns for big data analytics deployments, dealing with time series data, and the notion of the contextual enterprise.
Big data analytics use cases. IBM has identified five big data use cases from studying hundreds of engagements it has done across 15 different industries. These high value use cases include:
- 360 degree view of a customer- utilizing data from internal and external sources such as social chatter to understand behavior and “seminal psychometric markers” to gain insight into customer interactions.
- Security/Intelligence- utilizing data from sources like GPS devices and RFID tags and consuming it at a rate to protect individual safety from fraud or cyber attack.
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