AWS Data Lakes Best Practices on AWS Cloud (AWS Tutorial)

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Today, organizations find themselves in a data-rich world with a growing need for increased agility and access to data analysis from which they can derive keen insights and drive strategic decisions. Creating a data lake helps you manage all the disparate sources of data you are collecting in their original format and extract value. In this session, learn how to architect patterns to make data accessible to users, including governance, search, partitioning and columnar formatting.

AWS provides many services that are designed to help you take advantages of the business and financial benefits associated with running scalable workloads in the AWS Cloud. Knowing how to utilize these services to build highly available, fault tolerant and cost efficient applications often requires deep AWS expertise that can be hard to find. During this webinar, two of our AWS experts will tap into over 15 years of combined cloud experience to outline common design patterns and best practices associated with cost effectively scaling your AWS infrastructure.

Large object storage repositories, or data lakes, give us the ability to run big data analytics at larger scale than ever before. However, querying across larger data lakes can reduce performance and increase cost. Amazon S3 Select and Amazon Glacier Select are new AWS object storage features designed to filter and retrieve only the data you need from an object. These features allow queries to run directly on data stored in Amazon S3 or Amazon Glacier. These features allow you to increase application performance by up to 400% and reduce total cost of ownership by extending your data lake into cost-effective archive storage. In this webinar, we’ll discuss key considerations when you build your data lake in AWS object storage and how to use Amazon S3 Select and Amazon Glacier Select. We’ll also examine other query-in-place tools available in Amazon S3 like Amazon Athena and how S3 Select helps to accelerate its performance, as well.

Learning Objectives:
– Get an inside look at Amazon S3 Select and how it helps to accelerate application performance
– Learn about how Amazon Glacier Select helps you extend your data lake to archival storage
– Understand how different applications can leverage these features

By using a Data Lake, you no longer need to worry about structuring or transforming data before storing it. A Data Lake on AWS enables your organization to more rapidly analyze data, helping you quickly discover new business insights. Join us for our webinar to learn about the benefits of building a Data Lake on AWS and how your organization can begin reaping their rewards. In this webinar, select APN Partners will share their specific methodology for implementing a Data Lake on AWS and best practices for getting the most from your Data Lake.

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