Flexibility is key when building and scaling a data lake, and by choosing the right storage architecture you will have agility to quickly experiment and migrate with the latest analytics solutions. In this session, we explore the best practices for building a data lake on Amazon S3 that allows you to leverage an entire array of AWS, open-source, and third-party analytics tools, helping you remain at the cutting edge. We explore use cases for analytics tools, including Amazon EMR and AWS Glue, and query-in-place tools like Amazon Athena, Amazon Redshift Spectrum, Amazon S3 Select, and Amazon Glacier Select.