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LFS303: How to Build a Big Data Analytics Data Lake

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Content provided by AWS re:Invent 2016. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AWS re:Invent 2016 or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
For discovery-phase research, life sciences companies have to support infrastructure that processes millions to billions of transactions. The advent of a data lake to accomplish such a task is showing itself to be a stable and productive data platform pattern to meet the goal. We discuss how to build a data lake on AWS, using services and techniques such as AWS CloudFormation, Amazon EC2, Amazon S3, IAM, and AWS Lambda. We also review a reference architecture from Amgen that uses a data lake to aid in their Life Science Research.
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390 episodes

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Archived series ("Inactive feed" status)

When? This feed was archived on August 01, 2022 17:41 (1+ y ago). Last successful fetch was on January 04, 2017 18:46 (7+ y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 169376272 series 1333505
Content provided by AWS re:Invent 2016. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AWS re:Invent 2016 or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
For discovery-phase research, life sciences companies have to support infrastructure that processes millions to billions of transactions. The advent of a data lake to accomplish such a task is showing itself to be a stable and productive data platform pattern to meet the goal. We discuss how to build a data lake on AWS, using services and techniques such as AWS CloudFormation, Amazon EC2, Amazon S3, IAM, and AWS Lambda. We also review a reference architecture from Amgen that uses a data lake to aid in their Life Science Research.
  continue reading

390 episodes

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