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AWS-DATA-WH

Data Warehousing on AWS Training

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 Firehose, and Amazon S3. Additionally, this course demonstrates how to use business intelligence tools to perform analysis on your data.
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Course Details

Duration

3 days

Prerequisites

  • Completed AWS Technical Essentials course or have equivalent experience with AWS
  • Familiarity with relational databases and database design concepts

Target Audience

  • Database Architects
  • Database Administrators
  • Database Developers
  • Data Analysts
  • Data Scientists

Skills Gained

  • Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions
  • 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, and Amazon S3, to contribute to the data warehousing solution
  • Architect the data warehouse
  • Identify performance issues, optimize queries, and tune the database for better performance
  • Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket
  • Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse
Course Outline
  • Introduction to Data Warehousing
  • Introduction to Amazon Redshift
  • Launching Clusters
  • Designing the Database Schema
  • Identifying Data Sources
  • Loading Data
  • Writing Queries and Tuning Performance
  • Amazon Redshift Spectrum
  • Maintaining Clusters
  • Analyzing and Visualizing Data
Upcoming Course Dates
USD $2,185
Online Virtual Class
Scheduled
Date: May 28 - 30, 2024
Time: 9 AM - 5 PM ET
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