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AWS provides the most comprehensive set of services to move, store, & analyze your data, simplifying the process of setting up a data lake with a serverless architecture.
Come learn about data lake concepts & the AWS services that enable you to build a secure & efficient data lake, including more information on AWS Lake Formation, a service that simplifies creating & managing a secure data lake. We will also cover tools & services for processing & analyzing data in your data lake, & you'll get hands on experience with a variety of related AWS services in the labs.
This event is free to attendees. Please register to secure your seat.
Who should attend
Data Platform Engineers, Developers, Architects, & SysOps Admins who are eager to learn how to deploy Data Lakes on AWS. This event is best for attendees with a working knowledge of Databases & Analytics, as well as AWS services.
Please bring your laptop to participate in workshops, & make sure you have an active AWS account that you've logged into within one week of the event start date. Credits for workshop participation will be provided.
Schedule
9:30AM-10:00AM
Check In
Sign in, grab a badge, & get your seat.
10:00AM-10:15AM
Introduction to the AWS Loft & Data Lake Day
10:15AM-11:30AM
Building Data Lakes Using AWS Lake Formation
In this session we'll talk about why data lakes are needed, core principals/patterns for data lakes, & how AWS Lake Formation can help you simplify the process & reduce the time to build out a secure, well governed data lake on AWS.
Level: 300
11:30AM-1:30PM
Lunch & Lab: Building a Data Lake with AWS Lake Formation
Enjoy lunch, courtesy of Amazon.
In this workshop, gets hands on experience with setting up a data lake on AWS & configuring security & governance. Using AWS Lake Formation, you will ingest data into your new data lake, configure column-level permissions for your users, & query data with Amazon Athena.
Level: 300
1:30PM-2:30PM
Transforming & Processing Data in your Data Lake
,In this session we'll look at best practices for optimizing your data for analytics, including the use of optimized file formats like Parquet & common partitioning strategies. We will also discuss AWS services for processing & analyzing data in your data lake, including AWS Glue, Amazon Athena, Amazon EMR, Amazon Redshift Spectrum, & Amazon QuickSight.
Level: 300
2:30PM-4:30PM
Lab: Transforming & Processing Data in Your Data Lake
In this lab, we use various tools to transform & analyze the data in our data lake. We use AWS Glue to perform ETL on one of our data sets, Amazon Athena workgroups to manage our query sizes & costs, & Amazon QuickSight to create rich visualizations from data in the data lake.
Level: 300
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