Building Data Lakes on AWS

Kurskod GK7377

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.

Pris
9950 kr (exklusive moms)
Kursform
På plats

Leveransformer kan variera beroende på ort och datum.

På plats innebär att kursen hålls i klassrum. Läs mer här.
LiveClass innebär att kursen hålls som en lärarledd interaktiv onlineutbildning. Läs mer här.

Längd
1 dag
Ort och datum
13 dec
Live Online
4 jan
Live Online
14 mar
Live Online
23 maj
Live Online
25 jul
Live Online
3 okt
Live Online

Boka utbildning

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.


Target audience and prerequisites

This course is intended for:

  • Data platform engineers
  • Solutions architects
  • IT professionals

We recommend that attendees of this course have the following prerequisites:

  • Foundational knowledge about the AWS Platform equivalent to the course AWS Cloud Practitioner
  • One year of experience building data analytics pipelines 

Course objectives

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

Course details


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
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
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
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
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
Architecture and course review

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