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Course Objectives

This course is designed to teach you how to:

  • 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

Agenda

  • 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

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

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

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

  • 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

  • Preparing Data
  • Loading data using COPY
  • Data Warehousing on AWS
  • AWS Classroom Training
  • Concurrent write operations
  • Troubleshooting load issues
  • Hands-on lab 5: Loading data with the COPY command

  • 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

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

  • 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

  • Power of visualizations
  • Building dashboards
  • Amazon QuickSight editions and feature
Tags
Technical Core Type: Core 1 Vendor: Gilmore Global Product Line: AWS
FREE

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Course Type: Instructor Led