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From Big Data to Real-time Value: Streaming Operational Intelligence
Operational Intelligence is blurring the boundary between traditional BI analytics and the world of business operations. The two are no longer distinct business functions, rather a seamless continuum from streaming machine data to real-time business value. Existing log search and business intelligence systems struggle to deliver the required combination of real-time performance from high velocity data, sophisticated time and space-based analytics, and the operational integration required to drive automated action. Organizations in need of enterprise data management systems capable of identifying and predicting operational exceptions are faced with a wide range of Big Data technology options, each with different real-time and operational intelligence credentials. Understanding the technology and cost tipping points for each is key, and how technologies such as Hadoop, RDBMS and streaming differ in their cost of performance for real-time operational intelligence.
Damian Black – CEO
Now a CEO of SQLstream, Damian Black has over twenty-five years in the software infrastructure business. His career includes top positions with Hewlett-Packard, IP Mediation and Followap. Damian is the author of eleven patents and founder of SQLstream, a massively parallel real-time data engine executing continuous SQL queries against Streaming Big Data and supporting a cloud-based architecture.
SQLstream, Inc. empowers businesses to perform real-time analytics on unstructured log file, sensor and other machine-generated Big Data, through its distributed, 100% SQL platform for real-time data management and operational intelligence applications.
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