Building Data Lakes on AWS Training

Live Online & Classroom Enterprise Certification Training

Building Data Lakes on AWS is a course that teaches how to design, build, and manage scalable data lakes using AWS services like Amazon S3, AWS Glue, Lake Formation, and Athena for efficient data storage, cataloging, and analytics.

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What is Building Data Lakes on AWS Certification Training about?

In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures.

What are the objectives of Building Data Lakes on AWS Certification Training ?

In this course, you will learn to:

Apply data lake methodologies in planning and designing a data lake
CO1. Plan and design a data lake using established data lake methodologies.
CO2. Describe the components and services required for building a data lake on AWS.
CO3. Explain how to secure a data lake on AWS using appropriate permissions.
CO4. Compare the ways data can be ingested, stored, and transformed in a data lake on AWS.
CO5. Analyze and visualize data stored in a data lake on AWS.
CO6. Build and automate deployment of a data lake on AWS.
C07. Describe the role of a data lake within a modern data architecture.

Who is Building Data Lakes on AWS Certification Training for?

Data platform engineers
Solutions architects
IT professionals

What are the prerequisites for Building Data Lakes on AWS Certification Training?

We recommend that attendees of this course have:

Completed the AWS Technical Essentials classroom course
One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course

Available Training Modes

Live Online Training

Classroom Training

1 Days

Course Outline Expand All

Expand All

Module 1: Introduction to data lakes

Describe the value of data lakes

Compare data lakes and data warehouses

Describe the components of a data lake

Recognize common architectures built on data lakes

Module 2: Data ingestion, cataloging, and preparation

Describe the relationship between data lake storage and data ingestion

Describe AWS Glue crawlers and how they are used to create a data catalog

Identify data formatting, partitioning, and compression for efficient storage and query

Module 3: Building a Data Lake with AWS Lake Formation

Recognize how data processing applies to a data lake

Use AWS Glue to process data within a data lake

Describe how to use Amazon Athena to analyze data in a data lake

Lab 01: Building a Data Lake with AWS Lake Formation

Module 4: Data Processing and Analysis

Describe the features and benefits of AWS Lake Formation

Use AWS Lake Formation to create a data lake

Understand the AWS Lake Formation security model

Lab 2: Build a data lake using AWS Lake Formation

Module 5: Additional Lake Formation configurations

Explain the available built-in Blueprints to create and populate a new Lake Formation

Describe methods for applying advanced permissions to secure data access and workflow.

Describe fine-grained row/cell access control

Explain the Lake Formation Tag-based access control mechanism and the different use cases for Named access control vs. Tag-based access control

Describe access flow that enforces fine-grained access policies to both catalog metadata and underlying data resource for analytics services connecting to Lake Formation

Module 6: Modern Data Architecture

Explain capabilities of a modern data architecture: Scalable data lakes, Purpose-build analytics services, Seamless data movement, unified governance, and performance and cost-effectivness

Articulate the typical data movement within a modern data architecture: Inside out, Outside in, Around the perimeter, and Sharing across.

Describe focus of building and maintaining data products as a service.

Describe a typical Data Mesh architecture using Lake Formation and the key enablers supporting this methodology

Lab 3: Building and publishing a data product in Lake Formation

Module 7: Course Wrap Up

Post course knowledge check

Architecture review

Course review

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Who is the instructor for this training?

The trainer for this Building Data Lakes on AWS Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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