Given the rigorous demands that big data places on networks, storage and servers, it's not surprising that many customers are outsourcing the hassle and expense to the cloud. With AWS, you can provision exactly the right type and size of resources you need to power big data analytics applications. You can access as many resources as you need – almost instantly – and only pay for what you use.
However, supporting big data analysis in the cloud comes with a lot of architectural challenges, and the key to success is a deep understanding of the different components, services and architecture patterns that drive performance and consumption at scale.
At re:Invent, AWS will showcase and exhibit innovations to its broad portfolio of services that help customers rapidly build and deploy big data analytics applications quickly and easily. And in keeping with our principle to integrate beautifully with the technology choices our customers make, Tableau supports all of AWS’s innovations. Over the last couple of years, Tableau has launched direct connectors to all the major Amazon data sources including Amazon Redshift (and Redshift Spectrum), Amazon Athena, Amazon Aurora, Amazon EMR and Amazon RDS – all within a few months of their respective AWS launches.
Many of our largest customers including Expedia, Grab, Airbnb, and Pearson use the Tableau on AWS platform to innovate around how they collect, transform, store, process and analyze petabytes of data at scale. Several of them will be in attendance and share how they’re integrating different AWS components into their architecture in creative ways to drive different use cases.
In response to customer needs for architectural guidance Tableau has partnered with AWS to deliver automated Quickstarts (The Tableau AWS Modern Data Warehouse Quickstart & Tableau Server on AWS Quickstart). These Quickstarts simplify the process of launching, configuring, and running projects with the required AWS resources for compute, network, storage and other services while following best practices for security, availability and optimum query performance.
The Analytics & Big Data track at the Aria will provide best practices, architectural design patterns and in-depth discussions on Amazon Athena, Amazon Elastic MapReduce, Amazon Redshift, Amazon Kinesis, and a variety of other analytics services.
Watch this Big Data Strategy session for more on Tableau's own take on how to approach data architecture decisions for the enterprise including several “Tableau on AWS” examples.