Name: AWS Lake Formation
Rating: 7 (3 reviews)
Author: Amazon AWS

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### Data Storage and Management
Reviewers consistently highlight the ease of setting up a data lake with AWS Lake Formation, emphasizing its ability to streamline the process of storing and managing data efficiently. Users appreciate the platform's capability to centralize data from various sources, making it convenient for data analytics and decision-making purposes. The integration with a range of AWS services like EMR, Spark, Athena, and Redshift further enhances the appeal of AWS Lake Formation for data storage and management tasks. Additionally, the platform's support for different data formats such as Parquet and ORC contributes to faster and more efficient data analytics processes.

### Data Integration and Ingestion
Reviewers highlight the ease of use and speed at which AWS Lake Formation enables the creation of a structured data lake. The platform's ability to swiftly ingest data from multiple sources into Amazon S3, while offering data cleaning functionalities through connected AWS services like Redshift, Glue, and Athena, is widely appreciated. Users find the support for various data formats such as Parquet and ORC beneficial for accelerating data analytics processes. However, some users express concerns about the complexity that arises with different types of datasets and suggest improvements in data orchestration and image processing capabilities.

### Data Cataloging and Search
Users appreciate the ease of creating a data lake with AWS Lake Formation, highlighting the platform's ability to automatically pull data from specified sources and store it efficiently in S3 tables. The integration with various services like AWS EMR, Spark, Athena, and Redshift adds to its appeal, making it a compelling choice for data analytics tasks. The data catalog feature is particularly lauded for its user-friendly interface, enabling analytics teams to quickly access and utilize preferred datasets. Additionally, the fine-grained access control over data catalog tables enhances data governance and security within the platform.

### Security and Access Control
Users consistently highlight the robust security measures and fine-grained access control provided by AWS Lake Formation. They appreciate the ease of setting up secure data lakes and the secure storage of large amounts of data for business purposes. The platform's encryption capabilities and password protection are commended for enhancing data security and preventing unauthorized access. Additionally, users find the access control features beneficial in managing data access and implementing security protocols effectively. Despite some minor concerns, overall sentiment leans towards AWS Lake Formation being a reliable solution for ensuring data security and access control in a cloud environment.

AWS Lake Formation is a service designed to make it easy to set up a secure data lake in days. Creating a data lake with Lake Formation consists of defining data sources and what data access and security policies desired.

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Databricks in San Francisco offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service aims to provide a reliable and scalable platform for data pipelines, data lakes, and data platforms. Users can manage full data journey, to ingest, process, store, and expose data throughout an organization.  Its Data Science Workspace is a collaborative environment for practitioners to run all analytic processes in one place, and manage ML models across the full lifecycle. The Machine Learning Runtime (MLR) provides data scientists and ML practitioners with scalable clusters that include popular frameworks, built-in AutoML and optimizations.

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AWS Lake Formation

Data preparation tools are a new class of software products designed to enable business analysts and data scientists to bypass data warehouses to perform some data integration and data preparation themselves before analysis.

Data Preparation

Financial Services institutions are collecting an unprecedented amount of data but for most, legacy infrastructure, siloed data storage, and analytics tools don’t provide the agility and flexibility needed. By building a data lake on AWS, they can integrate multiple data sources into a consistent data set that is readily available to be categorized and processed. AWS data lakes make it easy to leverage AWS analytics to identify operational efficiencies, ensure compliance, and gain deeper customer insights to drive innovation. Join our tech talk to see a demo of AWS Lake Formation and deep-dive data lake reference architectures that will help optimize your data quality pipeline, master data management, and data protection.

Learning Objectives: 
*Understand key security considerations that Financial Services institutions must focus on as they build their data lakes on AWS 
*Review proven patterns based on actual data lakes deployed by Financial Services customers on AWS 
*Understand how AWS Lake Formation features, including the new permission model, can help Financial Services Institutions secure their data lakes with fine-grained access controls

***To learn more about the services featured in this talk, please visit: https://pages.awscloud.com/Financial-services-data-analytics-modernization.html

Building a Data Lake on AWS for Financial Services Institutions - AWS Online Tech Talks

AWS re:Invent 2019: Upgrading AWS Glue to use AWS Lake Formation permissions (DEM149)

ETL | Amazon RDS PostgreSQL Incremental Database to S3 Bucket Using AWS Lake Formation Blueprints

Authorizing Presto with AWS Lake Formation - Jalpreet Singh Nanda, Ahana & Roy Hasson, Amazon

AWS Lake Formation is a service that allows data platform users to set up a secure data lake in days. Creating a data lake with Presto and Lake Formation is as simple as defining data sources and what data access and security policies you want to apply. At Ahana and Amazon, engineers are working on Presto and Lake Formation integration to support Authorization on Presto. This means that Presto clusters will be enforce data permissions on user queries against Lake Formation backed data lakes, which is a tightly integrated Lake Formation, AWS Glue, and Amazon S3 data lake stack. In this session we will present high level design, our leanings, future plans and demo how data platform users can use Lake Formation integration to support fine-grained data access controls on Presto.

For more info about Presto, an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes, see: https://prestodb.io/H

Authorizing Presto with AWS Lake Formation - Jalpreet Singh Nanda, Ahana & Roy Hasson, Amazon

Demo of Catalog & Entity Details with Zaloni Arena Concourse

Getting Started with AWS Lake formation Managed Table and Fine grained access control

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AWS Lake Formation

Overview

What is AWS Lake Formation?