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Data Warehousing on AWS 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 AWS. This 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, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data.

Target Audience

Database architects
Database administrators
Database developers
Data analysts and scientists

Delivery Method

This course is delivered through a mix of:

Instructor-Led Training (ILT)
Hands-On Labs

Hands-On Activity

This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.

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

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

Day 1

Course Introduction
Introduction to Data Warehousing
Introduction to Amazon Redshift
Understanding Amazon Redshift Components and Resources
Launching an Amazon Redshift Cluster

Day 2

Choosing a Data Warehousing Approach
Identifying Data Sources and Requirements
Architecting the Data Warehouse
Loading Data into the Data Warehouse

Day 3

Optimizing Queries and Tuning Performance
Monitoring and Auditing the Data Warehouse
Maintaining the Data Warehouse
Analyzing and Visualizing Data

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

Other

How many employees do you have in your IT department?

0 – 50

50 – 250

250 – 1000

1000+

Upcoming Trainings

Join our public courses in our Singapore facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

27 November 2024