Many data analytic workflows can benefit from a reduction in time to results. With powerful compute resources and virtually infinite storage solutions offered affordably via the cloud it is now possible to build systems capable of pulling in & processing real-time data streams. However, many of these workflows still require custom development and custom builds. Amazon has released Kinesis, a Managed Service to ingest, process and store endless real-time data streams and do so even at massive scale. The movement from batch processing to real-time streams has already begun for many applications. Ad-tech, Gaming, Mobile App, Web App and Internet of Things (connected device) customers as well as plain old IT infrastructure are already generating endless data streams and leveraging Kinesis to generate new intelligence and competitive advantage by processing those streams in near real-time. Eric Heikkila will be in town from Seattle to host this Meetup to provide an overview of Kinesis, the problems it can help you to solve, the architecture of Kinesis and how it can be applied to common use cases. Integration with our Hadoop/EMR platform will be discussed as well as our latest support for Impala.
Please join us for an open and lively discussion on next generation stream processing. Your Speaker: Eric Heikkila, AWS Business Development Manager – Big Data
Eric works to educate and enable AWS customers on the AWS Big Data product portfolio. His focus is on both batch processing and real-time streaming solutions as he directly supports the AWS Elastic MapReduce and Kinesis product lines. Eric loves helping AWS customers to tame the ‘Zoo’ of Hadoop applications, to bring efficiency and true scalability to their big data workflows through cloud architectures and to explore the brave new world of broadly deployed real-time streams. Prior to AWS Eric was Director of the Embedded Computing Systems practice at the boutique strategy consulting firm VDC Research Group where he covered the nascent roll-out of the Internet of Things.
Lunch will be provided.