Why Do We Need a Data Lake?
we live in a digital era, where data volumes are increasing day-by-day, and organization needs a database that scales well for their massive data before use.
Data lakes come out as a cost-effective solution for big data, these efficiently handle large quantities of data. Data lake allows to store your data in its original form. So, when we are dealing with a large amount of data, we need data lake for querying and analyzing the big data.
How to Create AWS Data Lake
In the data-driven world, organizations are flooded with large amounts of data that originate from various sources, ranging from structured databases to unstructured files and logs. In order to effectively make use of this data for insights and decisions, organisations need to have a storage system that is capable of storing vast datasets. To address this challenge completely, AWS Data Lakes offers an all-inclusive solution as it enables centralized ingestion, cataloguing and querying at scale. By incorporating AWS services such as Amazon S3 Bucket, AWS Glue, AWS Lake Formation, AWS Athena and IAM together in a reasonable manner an organisations can build an elastic data lake architecture that allows for user-driven acquisition of actionable intelligence from their data while maintaining security and compliance standards.