Data Warehousing on AWS (DWAWS)

 

Course Overview

Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift. This course demonstrates how to ingest, store, and transform data in the data warehouse. Topics covered include: the purpose of Amazon Redshift, how Amazon Redshift addresses business and technical challenges, features and capabilities of Amazon Redshift, designing a Data Warehousing Solution on AWS by applying best practices based on the Well-Architected Framework, integration with AWS and non-AWS products and services, performance tuning, orchestration, and securing and monitoring Amazon Redshift.

Who should attend

This course is intended for:

  • Data engineers
  • Data architects
  • Database architects
  • Database administrators
  • Database developers

Prerequisites

We recommend that attendees of this course have completed the following courses:

  • Fundamentals of Analytics on AWS – Part 1 (Digital course)
  • Fundamentals of Analytics on AWS – Part 2 (Digital course)
  • Building Data Lakes on AWS ! (Instructor led Training)
  • Building Data Analytics Solutions Using Amazon Redshift Building Data Analytics Solutions Using Amazon Redshift (BDASAR) (Instructor led Training)

Course Objectives

In this course, you will learn to:

  • Describe Amazon Redshift architecture and its roles in a modern data architecture
  • Design and implement a data warehouse in the cloud using Amazon Redshift
  • Identify and load data into an Amazon Redshift data warehouse from a variety of sources
  • Analyze data using SQL QEV2 notebooks
  • Design and implement a disaster recovery strategy for an Amazon Redshift data warehouse
  • Perform maintenance and performance tuning on an Amazon Redshift data warehouse
  • Secure and manage access to an Amazon Redshift data warehouse
  • Share data between multiple Redshift clusters in an organization
  • Orchestrate workflows in the data warehouse using AWS Step Functions state machines
  • Create an ML model and configure predictors using Amazon Redshift ML

Prices & Delivery methods

Online Training

Duration
3 days

Price
  • on request
Classroom Training

Duration
3 days

Price
  • on request

Click on town name or "Online Training" to book Schedule

Europe

Germany

Berlin
Hamburg
Munich
Berlin
Frankfurt

France

Paris

Italy

Online Training Time zone: Central European Summer Time (CEST) Course language: Italian
Online Training Time zone: Central European Summer Time (CEST) Course language: Italian

Poland

Online Training Time zone: Central European Time (CET) Course language: Polish
Online Training Time zone: Central European Summer Time (CEST) Course language: Polish
Online Training Time zone: Central European Summer Time (CEST) Course language: Polish
Online Training Time zone: Central European Time (CET) Course language: Polish

Switzerland

Zurich
Zurich
Zurich
Zurich
Zurich
Zurich

United Kingdom

Online Training Time zone: Greenwich Mean Time (GMT) Course language: English
Online Training Time zone: Greenwich Mean Time (GMT) Course language: English
Online Training Time zone: British Summer Time (BST) Course language: English
Online Training Time zone: British Summer Time (BST) Course language: English
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.
This is a FLEX course, which is delivered both virtually and in the classroom.