Data Warehousing on AWS

You will be introduced to concepts, strategies and best practices for designing cloud-based data warehousing solutions using Amazon RedShift. The course also teaches you how to collect, store and analyze data for the data warehouse by using AWS services.

  • Live Demonstrations
  • Group Discussions
  • Frequent Knowledge Checks
  • Hands-On Labs
  • Database Architects
  • Database Administrators
  • Database Developers
  • Data Analysts
  • Data Scientists

Module 1: Introduction to Data Warehousing

  • Relational databases
  • Data warehousing concepts
  • The intersection of data warehousing and big data
  • Overview of data management in AWS
  • Hands-on lab 1: Introduction to Amazon Redshift

Module 2: Introduction to Amazon Redshift

  • Conceptual overview
  • Real-world use cases
  • Hands-on lab 2: Launching an Amazon Redshift cluster

Module 3: Launching clusters

  • Building the cluster
  • Connecting to the cluster
  • Controlling access
  • Database security
  • Load data
  • Hands-on lab 3: Optimizing database schemas

Module 4: Designing the database schema

  • Schemas and data types
  • Columnar compression
  • Data distribution styles
  • Data sorting methods

Module 5: Identifying data sources

  • Data sources overview
  • Amazon S3
  • Amazon DynamoDB
  • Amazon EMR
  • Amazon Kinesis Data Firehose
  • AWS Lambda Database Loader for Amazon Redshift
  • Hands-on lab 4: Loading real-time data into an Amazon Redshift database

Module 6: Loading data

  • Preparing Data
  • Loading data using COPY
  • Maintaining tables
  • Concurrent write operations
  • Troubleshooting load issues
  • Hands-on lab 5: Loading data with the COPY command

Module 7: 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)
  • Hands-on lab 6: Configuring workload management

Module 8: Amazon Redshift Spectrum

  • Amazon Redshift Spectrum
  • Configuring data for Amazon Redshift Spectrum
  • Amazon Redshift Spectrum Queries
  • Hands-on lab 7: Using Amazon Redshift Spectrum

Module 9: Maintaining clusters

  • Audit logging
  • Performance monitoring
  • Events and notifications
  • Lab 8: Auditing and monitoring clusters
  • Resizing clusters
  • Backing up and restoring clusters
  • Resource tagging and limits and constraints
  • Hands-on lab 9: Backing up, restoring and resizing clusters

Module 10: Analyzing and visualizing data

  • Power of visualizations
  • Building dashboards
  • Amazon QuickSight editions and features
Why choose Cloud Wizard
  • Advanced Tier Training Partner
  • Amazon Authorised Instructors
  • Official AWS Content
  • Hands-on Labs
Class Deliverables
  • E-Content kit by AWS
  • Hands-on labs
  • Class completion certificates
  • Exam Prep sessions

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