Data Warehousing on AWS

Course Code: 3012

Overview
Schedule classes
What you'll learn
Outline
Prerequisites
Who should attend

Overview

The Data Warehousing on AWS course introduces participants to concepts, strategies and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. The course guides participants how to collect, store and prepare data for the data warehouse by using other AWS services, such as, Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose and Amazon S3. The course also demonstrates how to use business intelligence tools to analyze data.

Schedule Classes

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Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 3 days

Live Virtual Classroom
Duration: 3 days

What You'll learn

Discuss the core concepts of data warehousing.
Evaluate the relationship between Amazon Redshift and other big data systems.
Evaluate use cases for data warehousing workloads and review case studies that demonstrate implementation of AWS data and analytic services as part of a data warehousing solution.
Choose an appropriate Amazon Redshift node type and size for your data needs.
Discuss security features as they pertain to Amazon Redshift, such as encryption, IAM permissions, and database permissions.
Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud.
Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon S3, to contribute to the data warehousing solution.
Evaluate approaches and methodologies for designing data warehouses.
Identify data sources and assess requirements that affect the data warehouse design.
Design the data warehouse to make effective use of compression, data distribution, and sort methods.
Load and unload data and perform data maintenance tasks.
Write queries and evaluate query plans to optimize query performance.
Configure the database to allocate resources such as memory to query queues and define criteria to route certain types of queries to your configured query queues for improved processing.
Use features and services, such as Amazon Redshift database audit logging, Amazon CloudTrail, Amazon CloudWatch, and Amazon Simple Notification Service (Amazon SNS), to audit, monitor, and receive event notifications about activities in the data warehouse.
Prepare for operational tasks, such as resizing Amazon Redshift clusters and using snapshots to back up and restore clusters.
Use a business intelligence (BI) application to perform data analysis and visualization tasks against your data.

Outline

Module 1

Introduction to data warehousing
Introduction to Amazon Redshift
Launching clusters

Module 2

Designing the database schema
Identifying data sources
Loading data

Module 3

Writing queries and tuning performance
Amazon Redshift spectrum
Maintaining clusters
Analyzing and visualizing data

Prerequisites

Participants need to have taken the AWS Technical Essentials course or have equivalent experience working with AWS. Participants need to be familiar with relational databases and database design concepts.