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MEETUP SUMMARY

There is a growing need to have access to information for decision making faster than ever before. And part of this is because companies are looking to capitalize on insights that can only be gained from data while it is in motion; perishable information that is time sensitive and may not have value by the time it lands in an enterprise data store or lake. Stream processing technologies provide a framework for building applications that continuously run analysis on data in motion. However the complexity involved in designing, developing, and operationalizing streaming applications require specific skill sets and may lead to extensive delivery timelines which lengthen the time for companies to realize value from these systems.

Streaming Analytics Manager (SAM) was created to simplify the development and reduce the delivery time of analytic applications geared towards data in motion. Using a drag-and-drop interface, application developers can create complex streaming analytics apps for event correlation, context enrichment, and complex pattern matching; eliminating the need for specialized skillsets. SAM also provides the concepts of service pools and environments, which help users easily define the streaming technologies and environments their application will use for execution, and a streaming operations view to give users insight into their application’s performance during runtime. With SAM as an analytics solution, users will get a rich experience for building and managing streaming analytics applications and bring these applications to market considerably faster.

Join us as Yolanda Davis, Senior Software Engineer and Streaming Team Lead at Hortonworks once again gives us the latest in Big Data and Streaming Technologies using SAM. During this seminar we will discuss how SAM fits into the overall solution for Hortonworks DataFlow Platform, review fundamental stream processing concepts and, demonstrate SAM’s capabilities in the context of a familiar use case for streaming analytics.

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