Building Data Lakes on AWS- Course Overview

Building Data Lakes on AWS helps learn how to build an operational data lake to analyze both structured and unstructured data. Taking up this training on building Data Lakes on AWS, candidates are trained to use the various components and features of AWS services to create a data lake.

This Building Data Lakes on AWS training teaches candidates how to use AWS Glue to build a data catalog, AWS Lake Formation to build a data lake, and Amazon Athena to analyze data. The course comprises presentations, lectures, hands-on labs, and group exercises.

After completing Building Data Lakes on AWS, students will be able to

  • Apply data lake methodologies in planning and designing a data lake
  • Articulate the components and services required for building an AWS data lake
  • Secure a data lake with appropriate permission
  • Ingest, store, and transform data in a data lake
  • Query, analyze, and visualize data within a data lake

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Building Data Lakes on AWS- Key Features

  • Building Data Lakes on AWS has hands-on labs to encourage Thinking-Based Learning (TBL).

  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).

  • The course is taught by AWS Authorized Instructors to ensure quality delivery.

  • Well-structured use-cases to simulate challenges encountered in a Real-World environment.

  • Being an authorized AWS Training Partner gives us an edge over the competition.

Who should attend Building Data Lakes on AWS?

  • Data platform engineers
  • Solutions architects
  • IT professionals

Building Data Lakes on AWS- Prerequisites

We recommend that attendees of Building Data Lakes on AWS 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

Building Data Lakes on AWS- Course Outline Download Course Outline

  • 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

  • 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

  • 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

  • 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
  • Understand the AWS Lake Formation security model
  • Lab 2: Build a data lake using AWS Lake Formation

  • 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

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

  • Post course knowledge check
  • Architecture review • Course review

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Course ID: 13498

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