AWS re:Invent 2019 is only a few weeks away and promises to be a huge event with more sessions on Databases and Analytics than ever before.
Since there is so much on offer I've put together the sessions, chalk talks and workshops I'm most excited about. I hope you find them interesting too.
This session covers the latest improvements to Athena, the serverless query service. I'm looking forward to hearing more about concurrency, security and query performance.
Earlier in the year AWS announced that Redshift now supports SQL stored procedures to make migration and processing on Redshift easier. Up until now we had to provision another system like SQL Server to create scheduled jobs, in this talk we'll learn how to get up and running using Redshift.
Alex DeBrie, creator of DynamoDBGuide.com and an AWS Data Hero, will be running this session. We'll learn the principles and steps to follow to model and structure data for DynamoDB.
The team from Warner Bros will be leading this talk on how Redshift handles small datasets with large bursts of query activity, large datasets with complex queries, a mix of frequently queried data and infrequently accessed historical data.
The story of how Amazon.com moved from Oracle to a scalable, AWS-based data lake in less than two years leveraging Amazon Redshift and Amazon EMR.
Gone are the days of simply batch processing. Streaming data is the best way to react to customer demands and speed up decision making. In this session GoDaddy shares how they use this architectural pattern to provide the best experience to the millions of customers that host websites on their platform.
In this session the team from The Pokémon Company discuss best practices for migration and give us a glimpse into the services supporting Pokémon Go, including AWS Lambda, Amazon Kinesis, Amazon Redshift, and more.
This Builders Session is designed to be hands on and an introduction to trouble shooting as well as deploying solutions. Learn how to manage, monitor, and scale your data warehouse quickly and easily. You also learn how to deploy and scale multiple independent clusters, and scale each independently to address different workload scenarios.
This workshop covers the basics of this tiered storage model and outlines design patterns that you can leverage to get the most from large volumes of data. Learn how to build out your own Amazon Redshift cluster with multiple data sets to illustrate the trade-offs between the storage systems. Learn how to distribute your data and design your DDL to deliver the best data warehouse for your business.
In this Builders Session, we discuss tips and best practices to optimise Amazon Redshift with popular BI tools.
This small-group, hands-on exercise is a guided tour of how to create and run serverless extract, transform, and load (ETL) functions on AWS Glue. Learn how to work with both Apache Spark jobs and Python shell scripts to manage data integration for analytics.
Are you going to re:Invent this year? Which sessions are you most looking forward to checking out?
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