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AWS Authorized Training Course - Data Warehousing on AWS

Course Summary

The Data Warehousing on AWS training course is designed to demonstrate the concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift.

The course examines how to collect, store, and prepare data for the data warehouse. Next, it evaluates how to use AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. The course concludes by exploring how to use Amazon QuickSight to perform analysis on your data.

AWS Authorized Training is only available in Argentina, Brazil, Canada, Chile, Colombia, Costa Rica, Mexico, United States, and Peru.

THIS COURSE IS NOT ELIGIBLE FOR TRAINING BUNDLES.

Purpose
 How to a cloud-based data warehousing solution using Amazon Redshift
Audience
 Database Architects, Database Administrators, Database Developers, Data Analysts and Data Scientists
Role
Data Engineer - Data Scientist
Skill Level
Intermediate
Style
Workshops
Duration
3 Days
Related Technologies
Amazon DynamoDB | Cloud Computing Training | AWS

 

Productivity Objectives
  • 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
  • Utilize Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse

What You'll Learn:

In the AWS Authorized Training Course - Data Warehousing on AWS training course, you'll learn:
  • Introduction to Data Warehousing
    • Relational databases
    • Data warehousing concepts
    • The intersection of data warehousing and big data
    • Overview of data management in AWS
    • Introduce Amazon Redshift Lab
  • Introduction to Amazon Redshift
    • Conceptual overview
    • Real-world use cases
    • Launch an Amazon Redshift cluster Lab
  • Launching Clusters
    • Build the cluster
    • Connect to the cluster
    • Control access
    • Database security
    • Load data
    • Optimize database schemas
  • Designing the Database Schema
    • Schemas and data types
    • Columnar compression
    • Data distribution styles
    • Data sort methods
  • Identifying Data Sources
    • Data sources overview
    • Amazon S3
    • Amazon DynamoDB
    • Amazon EMR
    • Amazon Kinesis Data Firehose
    • AWS Lambda Database Loader for Amazon Redshift
    • Load real-time data into an Amazon Redshift database Lab
  • Loading Data
    • Prepare Data
    • Load data with COPY
    • Maintain tables
    • Concurrent write operations
    • Troubleshoot load issues
    • Load data with the COPY command
  • Writing Queries and Tuning for Performance
    • Amazon Redshift SQL
    • User-Defined Functions (UDFs)
    • Factors that affect query performance
    • The EXPLAIN command and query plans
    • Workload Management (WLM)
    • Configure workload management Lab
  • Amazon Redshift Spectrum
    • Amazon Redshift Spectrum
    • Configure data for Amazon Redshift Spectrum
    • Amazon Redshift Spectrum Queries
    • Utilize Amazon Redshift Spectrum Lab
  • Maintaining Clusters
    • Audit log
    • Performance monitor
    • Events and notifications
    • Audit and monitor clusters Lab
    • Resize clusters
    • Back up and restore clusters
    • Resource tags and limits and constraints
    • Back up, restore and resize clusters Lab
  • Analyzing and Visualizing Data
    • Power of visualizations
    • Build dashboards
    • Amazon QuickSight editions and features
real world content

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
expert practitioners

Expert Practitioners

Industry experts that bring their battle scars into the classroom.
experiential learning

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
tailored outlines

Tailored Outlines

One-size-fits-all doesn't apply to training teams. That's where we come in!
“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”

VMware

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