AWS

Building Data Lakes

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Course Overview

In this 1 day, instructor led course, participants 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. At the completion of this course, participants 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

Schedule

Currently, there are no public classes scheduled. Please contact a Phoenix TS Training Consultant to discuss hosting a private class at 301-258-8200.

Program Level

Advanced

Training Delivery Methods

Group Live

Duration

1 Days / 8 hours Training

CPE credits

6 NASBA CPE Credits

Field of Study

Information Technology

Advanced Prep

N/A

Course Registration

Candidates can choose to register for the course by via any of the below methods:

Email: Sales@phoenixts.com
Phone: 301-582-8200
Website: www.phoenixts.com

Upon registration completion candidates are sent an automated course registration email that includes attachments with specific information on the class and location as well as pre-course study and test preparation material approved by the course vendor. The text of the email contains a registration confirmation as well as the location, date, time and contact person of the class. Online enrolment closes three days before course start date. On the first day of class, candidates are provided with instructions to register with the exam provider before the exam date.

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Refunds and Cancellations

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Course 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

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
Lab 1: Set up a simple data lake

Module 3: Data processing and analytics

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

Module 4: 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
Lab 2: Build a data lake using AWS Lake Formation

Module 5: Additional Lake Formation configurations

Automate AWS Lake Formation using blueprints and workflows
Apply security and access controls to AWS Lake Formation
Match records with AWS Lake Formation FindMatches
Visualize data with Amazon QuickSight
Lab 3: Automate data lake creation using AWS Lake Formation blueprints
Lab 4: Data visualization using Amazon QuickSight

Module 6: Architecture and course review

Post course knowledge check
Architecture review
Course review

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