Want to ramp up your knowledge of Amazon’s big data web services and launch your first big data application on the cloud? Ian Meyers, Pratim Das, and Ian Robinson walk you through simplifying big data processing as a data bus comprising ingest, store, process, and visualize and building a big data application in real time using a combination of open source technologies, including Apache Hadoop, Spark, and Zeppelin, as well as AWS managed services such as Amazon EMR, Amazon Redshift, Amazon Kinesis, and Amazon S3. Along the way, they review architecture design patterns for big data applications and give you access to a take-home lab so that you can rebuild and customize the application yourself.
Ian Meyers is a principal solution architect at AWS, where he manages the Specialist Solution Architecture team in EMEA. He has a background in data management systems—specifically data warehousing, big data, and event-driven architectures—in the financial services, communications, and gaming industries.
Pratim Das is Head of Solutions Architecture (Data & AI) for Microsoft UK, where he a team of solutions architects focused on Data & AI, and geared towards customer success. Prior to that he was at AWS as a Specialist SA for Big Data & Analytics, where he advised customers on big data architecture, migration of big data workloads to the cloud, and implementing best practices and guidelines for analytics and works with customers on advanced analytics, such as building predictive models, image recognition, NLP, and smart cities.
Ian Robinson is a specialist solutions architect for data and analytics at AWS, where he works with customers throughout EMEA, helping them use AWS to create value from the connections in their data. Ian is a coauthor of Graph Databases and REST in Practice (both from O’Reilly) and a contributor to REST: From Research to Practice (Springer) and Service Design Patterns (Addison-Wesley).
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