AWS Lake Formation

Benefits of using the AWS Lake Formation Service

Using AWS Lake Formation has the following set of capabilities and perks that it offers to its user:

Build data lakes quickly

• Using the Lake Formation service one can move, store, catalogue, and clean data faster. 
• One can simply point the Lake Formation to the data sources, and it is capable of reliably fetching crawled data from those sources and then moving the data into the new Amazon S3 data lake. 
• It organizes the data in S3 around frequently used query terms and into right-sized chunks to increase efficiency. It also changes all the data into formats such as Apache Parquet and ORC for faster analytics. 
• Since it has built-in ML functionalities and services to deduplicate and find matching records and to enhance the data quality which can be used along with multiple third party or other AWS analytics services.

Simplify security management

• The AWS Lake Formation service provides a single place to define and enforce access controls that operate at the table, column, row, and even cell level for all the users and services that access the data. The policies in it are consistently implemented, also eliminating the need to manually configure them across various security services such as the AWS Identity and Access Management (IAM) and AWS Key Management Service (KMS), storage services such as S3, and analytics and ML services such as Redshift, Athena, AWS Glue, and EMR for Apache Spark. 
• Using Lake Formation reduces the efforts in configuring policies across various services and provides consistent enforcement and compliance across them.

Provide self-service access to data

• With The Lake Formation service, one can build a data catalogue that describes the multiple datasets available, in addition to the groups of users that have access to each. 
• This makes the users more productive by helping them find the right dataset for analyses. 
• By providing a catalogue of the data with consistent security enforcement, The AWS Lake Formation service makes it easier for analysts and data scientists to use their preferred analytics services. 
• They can use EMR for Apache Spark, AWS Glue, Redshift, Athena, and Amazon QuickSight on diverse datasets now housed in a data lake. Users can also combine all these services without having the need to move data between silos.

Use-Cases of using the AWS Lake Formation Service

There are several use-cases where the AWS Lake Formation services really shine such as the following few:

When there is a requirement for a Lake Formation on a short notice

• One can use blueprints available in a Lake Formation to move, store, catalogue, clean, and organize the data faster. 
• Convert data into formats multiple formats such as Parquet and ORC for faster analytics, and use the built-in ML to de-duplicate and find a set of matching records.
• Simplify how one store and maintains data using Governed Tables, a new type of Amazon S3 table. 
• Here, the governed tables use ACID (atomic, consistent, isolated, and durable) transactions that automatically manage conflicts and ensure consistent data views for all participating/involved users. 
• The Governed Tables also monitor and automatically optimise the data to improve engine performance when querying the Governed Tables.

When it is required of the system to be able to centrally define and manage access controls

• Lake Formation provides a single place to define, classify, tag, and manage fine-grained permissions for the data in Amazon S3 data lakes. 
• One can define a hierarchical list of tags, assign tags to databases, tables and columns, and configure column and cell-level security.

To enforce data classification and fine-grained access

• The Lake Formation service enforces policies without having to configure data access controls in each of the consuming services. 
• The Lake Formation service automatically filters data and only reveals data permitted by the defined policy to authorized users, without having to duplicate data.

To enable continuous data management, time travel, and storage optimization

• To enhance the reliability and trustworthiness of updating batch and streaming data in a data lake. 
• To query historical data versions and audit changed data. Auto-compact small files and enable push-down filters to reduce data scans and improve query performance.

Enable federated data lakes with cross-account sharing

• To deliver decentralized, domain-oriented data products across organizations using well-governed data sharing with minimal to no data movement.

Frequently asked questions

Are there any restrictions to using The AWS Lake Formation services in an AMS account?

No, there are no such restrictions and all the services and complete functionality of The Lake Formation are available in an AMS.

What are the prerequisites or dependencies to using an AWS Lake Formation service in an AMS account?

The Lake Formation service integrates with the AWS Glue service, therefore since the AWS Glue users can access only the databases and tables on which they have Lake Formation permissions. Additionally, AWS Athena and Amazon Redshift users can only query the AWS Glue databases and tables on which they have Lake Formation permissions.

Conclusion

AWS Lake Formation is a service that allows one to easily set up a secure data lake in a matter of a few days.

This article has covered the definition, benefits and usage of the AWS Lake Formation service.

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