Building Data Lakes on AWS

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.

Physisch oder virtuell?

Nehmen Sie an einem unserer Standorte Frankfurt, München und Wien oder virtuell an unseren Klassenraumtrainings teil. Unter „Termin buchen“ werden Ihnen alle Optionen angezeigt, zuerst sortiert nach Standort, dann nach Datum.

Dauer

Trainingssprache

Deutsch

Trainingsart

Nicht verfügbar

Was werden Sie in diesem Training erlernen?

In this course, you will learn 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

Agenda

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

Course review

REVIEWING ARCHITECTING CONCEPTS

SINGLE TO MULTIPLE ACCOUNTS

Group Exercise: Review Architecting on AWS core best practices
AWS Organizations for multi-account access and permissions
AWS SSO to simplify access and authentication across AWS accounts and third-party services
AWS Control Tower
Permissions, access, and authentication

HYBRID CONNECTIVITY

SPECIALIZED INFRASTRUCTURE

Zielgruppe

This course is intended for: Data platform engineers Solutions architects IT professionals

Voraussetzung für den Kurs

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

Partner

AWS