Percona Live: Data Performance Conference 2016 Logo

April 18-21, 2016

Santa Clara, California

AWS Big Data Services: Reimagining Big Data Processing in the Cloud

AWS Big Data Services: Reimagining Big Data Processing in the Cloud

 20 April 09:00 AM - 9:20 AM
Experience level: 
Intermediate
Duration: 
Keynote
Tracks:
Sponsored
Topics:
Other

Description

Find out about the data challenges and trends that drove AWS to reimagine data processing and bet the future on new Big Data services that are innovating data infrastructure from NoSQL databases to data warehouses. We believe that one size doesn’t fit all and multiple services are often necessary to address different challenges of Big Data. In this talk, I will provide an under the hood view of some of the most popular Big Data services at AWS including Amazon DynamoDB - a NoSQL service, Amazon Redshift - a peta-byte scale data warehouse service, Amazon EMR – an elastic map-reduce service, and Amazon Aurora - a massively scalable relational database service, all designed and optimized for the cloud. I will also talk about best practices in understanding customer desires and behavior from Big Data and how to achieve 1:1 customer experience at scale.

Speakers

Anurag Gupta's picture

Anurag Gupta

Vice President of Big Data Services, Amazon Web Services

Biography:

Anurag Gupta is the Vice President of Big Data Services at AWS and is responsible for strategy and execution of Amazon Redshift, Amazon Aurora, Amazon Elastic Map Reduce and AWS Data Pipeline. Prior to joining AWS, Anurag held multiple engineering management and technology leadership roles across low-level systems and applications at a range of company sizes - from large enterprises to start-ups. What's been consistent however is a bias towards high-growth environments, early-version products and deep IP. He joined Amazon because he believes that cloud computing has transformational potential and is at least as large a shift as minicomputer, client-server, and app-server based computing were for prior generations. He also believes that there is a need for significant rethinking within the data processing community as we move from a design point focused on the sharing of scarce system resources to one where the central challenge is how to take advantage of their abundance.

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