A recent press release reports, “Amazon Web Services, Inc. (AWS), an Amazon.com company, announced the general availability of AWS Lake Formation, a fully managed service that makes it much easier for customers to build, secure, and manage data lakes. AWS Lake Formation simplifies and automates many of the complex manual steps usually required to create a data lake, including collecting, cleaning, and cataloging data, and securely making that data available for analytics. Customers can easily bring their data into a data lake from a variety of sources using pre-defined templates, automatically classify and prepare the data, and centrally define granular data access policies to govern access by the different groups within an organization. Customers can then analyze this data using their choice of AWS analytics and machine learning services, including Amazon Redshift, Amazon Athena, and AWS Glue, with Amazon EMR, Amazon QuickSight, and Amazon SageMaker following in the next few months. There are no additional charges required to use AWS Lake Formation, and customers pay only for the underlying AWS services used. To get started with AWS Lake Formation, visit: https://aws.amazon.com/lake-formation.”
The release continues, “Customers want to be able to perform analytics and machine learning across all of their data, regardless of the format or where the data lives. A data lake removes data silos and allows data to reside in a central place so customers can more easily apply different types of analytics and machine learning across all of their data. Amazon Simple Storage Service (Amazon S3) has become a very popular place for customers to build data lakes because of its scale, cost-effectiveness, durability, and easy integration with AWS’s analytics and machine learning services. However, even with those significant benefits, building and managing a data lake can still be a complex and time-consuming process. Customers need to provision and configure storage, move data from disparate sources into the data lake, and extract the schema and add metadata tags to make it accessible from a searchable data catalog.”
Read more at Business Wire.
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