Data Warehousing on AWS

Course 1246

  • Duration: 3 days
  • Language: English
  • Level: Intermediate

This Data Warehousing on AWS course introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in Amazon Web Services (AWS). This AWS Data Warehousing course demonstrates 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. Additionally, this course demonstrates how to use business intelligence tools to perform analysis on your data.

Data Warehousing on AWS Delivery Methods

  • Official AWS training curriculum

  • Attend in-class or online

Data Warehousing on AWS Course Benefits

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

Data Warehousing on AWS Course Outline

Data Warehousing on AWS (DWAWS) Prerequisites

  • Courses taken: AWS Technical Essentials (or equivalent experience with AWS)
  • Familiarity with relational databases and database design concepts

Day 1

  • Introduction to Data Warehousing
  • Introduction to Amazon Redshift
  • Launching Clusters

Day 2

  • Designing the Database Schema
  • Identifying Data Sources
  • Loading Data

Day 3

  • Writing Queries and Tuning Performance
  • Amazon Redshift Spectrum
  • Maintaining Clusters
  • Analyzing and Visualizing Data

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Data Warehousing on AWS FAQs

You must take AWS Technical Essentials (or equivalent experience with AWS)

Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want. This course is available in class and live online.

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