Data Warehousing on AWS
New
Course description
Using Amazon Redshift, the petabyte-scale data warehouse in AWS, Data Warehousing on AWS exposes you to principles, techniques, and best practices for developing a cloud-based data warehousing system. This AWS course shows how to leverage AWS services, including Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to gather, store, and prepare data for the data warehouse. Additionally, this course shows you how to analyze your data using Amazon QuickSight.
Activities
The AWS data warehousing course includes the following activities:
- Live Demonstrations
- Group Discussions
- Frequent Knowledge Checks
- Hands-On Labs
Course Objectives
Intended Audience
Prerequisites
Module Breakdown
Course outline
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
FAQ's
Is Cloud Wizard Consulting an official AWS training partner?
Yes, we have been since 2015.
Who should take up this course?
You can take on this course if you belong to the following category of individuals:
- Database Architects
- Database Administrators
- Database Developers
- Data Analysts
- Data Scientists
What prior experience do you need for this course?
We recommend that attendees of this course have:
- Taken AWS Technical Essentials (or equivalent experience with AWS)
- Knowledge of relational databases and database design concepts