The power of the AWS Lake formation service is that it organizes a diverse collection of disconnected AWS services it an orchestrated configuration service.Īs a result, AWS lake formation is primarily focused on the orchestration of underlying AWS services into a cohesive interface and API. If you are a GCP or Azure customer, both have similar concepts for lake formation (though the process & tools vary).Īmazon says its lake formation is “a service that allows you to build a secure data lake in days.” In reality, a shell of the AWS lake may only take a few hours to complete. To establish a base pattern for a lake, drive consistency, and velocity, AWS established a formalized lake formation process. AWS Lake Formationĭoes a data lake have to be complex to set up? No! However, with an automated data lake formation process employed by AWS, GCP, and Azure, you can get up and running more quickly. In this post, we are focused on the AWS cloud, though many concepts will transcend an AWS deployment to GCP or Azure. We detailed several numerous misconceptions and myths about data lakes. Part of the challenge is various definitions that describe “ what is a data lake?” which can create confusion on best practices and productive outcomes.
If you read about data lakes, you will often come across a post, guide, documentation, or tweet that will describe setting up a data lake as creating an AWS S3 bucket, some paths, and then dropping files in. AWS Lake Formation: Accelerating Data Lake Adoption
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