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Starts 8 June 2025 14:02

Ends 8 June 2025

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Build a Secure Data Lake in AWS using AWS Lake Formation

Step by step guide for setting up a data lake in AWS using Lake formation, Glue, DataBrew, Athena, Redshift, Macie etc.
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4052 Courses


3 hours 18 minutes

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Overview

In this course, we will be creating a data lake using AWS Lake Formation and bring data warehouse capabilites to the data lake to form the lakehouse architecture using Amazon Redshift. Using Lake Formation, we also collect and catalog data from different data sources, move the data into our S3 data lake, and then clean and classify them.

Syllabus

  • Introduction to Data Lakes and Lakehouse Architecture
  • Overview of Data Lakes
    Understanding Lakehouse architecture
    Key concepts in AWS Lake Formation and Amazon Redshift
  • Setting up the AWS Environment
  • Introduction to AWS services needed
    Configuring AWS Identity and Access Management (IAM)
    Setting up AWS Simple Storage Service (S3) buckets
  • Introduction to AWS Lake Formation
  • Overview of AWS Lake Formation features
    Understanding Lake Formation permissions
  • Creating a Data Lake in AWS Lake Formation
  • Registering S3 locations
    Creating databases and tables in the data catalog
    Using Blueprints for data import
  • Data Ingestion and Cataloging
  • Collecting data from various sources
    Automating data movement into S3 using Lake Formation
    Cataloging data with AWS Glue
  • Data Cleaning and Classification
  • Data cleaning best practices
    Using transforms and classifiers in Lake Formation
    Ensuring data quality and consistency
  • Building Lakehouse with Amazon Redshift
  • Setting up Redshift clusters
    Integrating Redshift with Lake Formation
    Querying data across the data lake using Redshift Spectrum
  • Security and Access Management
  • Implementing granular data access controls
    Configuring data encryption and privacy settings
    Auditing and monitoring data activity
  • Advanced Topics in Lake Formation
  • Automating workflows with AWS Glue and Step Functions
    Implementing machine learning models in the data lake
  • Case Study and Hands-on Project
  • Real-world example of building a secure data lake
    Group project: Design and implement a mini-lakehouse architecture
  • Review and Next Steps
  • Best practices for maintaining a data lake
    Upcoming AWS features and updates in data lake technology
    Resources for further learning

Taught by

Yomi Owoyemi


Subjects

Business