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Deploying Batch and Streaming Architectures on AWS
Submitted by Russell Nash (@russnash) on Thursday, 18 June 2015
To learn about the key Big Data and Analytics services on AWS and how they can be used for both batch and streaming workloads.
One of the biggest challenges organizations face when designing Big Data platforms is analyzing historical, batch and streaming data using the same architecture.
This session will illustrate how to use AWS Big Data services such as Amazon Elastic MapReduce, Amazon Kinesis, Amazon Redshift and others to build a scalable, fault-tolerant and multi-layered processing system which includes the ability to analyze streaming data by comparing it against historical data in near real-time.
Russell Nash is a Solutions Architect with Amazon focused on data analytics.
He works with customers to derive maximum value and performance from using the Amazon data analytics services.
Russell has over 20 years experience in the IT industry and the majority of that time was spent working with database and parallel technologies designed for large scale analysis.
He is passionate about applying these technologies to business problems in order to return value and insight to organizations.