Building Data Lakes on AWS

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In this Building Data Lakes on AWS course, you will learn how to build an operational data lake that supports the 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.

Building Data Lakes on AWS Delivery Methods


Building Data Lakes on AWS Course Information

In this Building Data Lakes on AWS course, you will learn how 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.

Building Data Lakes on AWS Prerequisites

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.
Building Data Lakes on AWS Training Outline
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
Module 3: Data processing and analytics
Module 4: Building a data lake with AWS Lake Formation
Module 5: Additional Lake Formation configurations
Module 6: Architecture and course review

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