The Simple Storage Service (S3) of Amazon is a cloud-based data storage service where data in its native format like unstructured, semi-structured, or structured forms may be stored. The data has high durability of 99.999999999 (11 9s) and is kept in a highly secured and safe ecosystem.

Several competencies are used for creating an Amazon S3 data lake such as high-performance computing (HPC), big data analytics,Machine Learning (ML),media data processing applications, and Artificial Intelligence (AI). All these help to provide critical business analytics and intelligence from the S3 data lake and unstructured data sets.

Additionally, the S3 data lake through Amazon FSX for Luster processes large volumes of workloads using file systems for ML and HPC applications. The Amazon Partner Network (APN) applications like ML, HPC, and AI can also be used for specific analytics on the S3 data lake.

Several advantages are offered by theS3 data lake.

•There are separate silos for storage and computing on the S3 data lake where all types of data in their native formats can be kept. This is against traditional systems where they were closely interlinked, making it almost impossible to differentiate the costs of maintaining the two as well as estimating their efficiencies.

•Organizations can undertake data processing, querying, and implementation across serverless and non-cluster AWS services on the S3 data lake. The AWS platforms are Amazon Redshift Spectrum, AWS Glue, Amazon Athena, and Amazon Rekognition. On these serverless computing facilities, users can run codes without having to manage or provision servers. All these services can be availed by paying only for the extent of resources used without any flat or upfront charges.

•The centralized data structure of Amazon S3 allows a multi-tenant environment to be easily created to bring analytics tools under a common data set. This is a great advancement over older systems and their quality of governance where data copies had to be distributed over several data processing platforms.

•Amazon S3 data lake APIs are supported by numerous user-friendly third-party vendors like Amazon Hadoop and others, allowing users to select the tools they are most comfortable working with.

•Since large numbers of AWS analytics applications and high-performing file systems can be accessed by users of the S3 data lake, it is possible to run unlimited workloads and intricate queries without additional data processing capabilities.

•The S3 data lake can be built in days with the AWS Lake Formation as against months that used to be taken for building traditional data lakes. All that users have to do is to decide where the data is to be located and the policies to be applied for data access and security. Once this is done, The Lake Formation consolidates the data collected from different sources and moves it to the Amazon S3 data lake.

It is therefore seen that S3 data lake has complete infrastructure support from all ancillary Amazon Services.