Amazon Web Services (AWS)
Building Data Analytics Solutions using Amazon Redshift
Get hands-on with Amazon Redshift as your cloud data warehouse.
1 dayIntermediate8 modules
About this course
Get hands-on with Amazon Redshift as your cloud data warehouse. You will learn the architecture, load, model and query data, use Spectrum and federated queries, and manage security, monitoring and cost.
What you'll learn
- Understand Amazon Redshift architecture, key components and node types
- Load, model, and query data with Redshift SQL
- Use Redshift Spectrum and federated queries for external access
- Apply cost management to enhance Redshift performance and efficiency
Curriculum
8 modules
- Explore common use cases for data analytics
- Understand how the data pipeline supports analytics at scale
- Learn why Amazon Redshift is used for cloud data warehousing
- Get an overview of Amazon Redshift’s core capabilities
- Understand the architecture and components of Amazon Redshift
- Interactive Demo 1: Navigate the Amazon Redshift console
- Explore key Redshift features and functionalities
- Practice Lab 1: Load and query data in a Redshift cluster
- Discover methods for ingesting data into Amazon Redshift
- Interactive Demo 2: Connect to a Redshift cluster using a Jupyter notebook with the Data API
- Learn how Redshift handles data distribution and storage
- Interactive Demo 3: Work with semi-structured data using the SUPER data type
- Explore how Redshift supports efficient querying across storage types
- Practice Lab 2: Analyze data using Amazon Redshift Spectrum
- Perform data transformations using SQL in Amazon Redshift
- Apply advanced querying techniques for complex analytics workloads
- Practice Lab 3: Transform and analyze data in Redshift
- Manage resources with workload management (WLM) features
- Interactive Demo 4: Apply mixed workload management settings
- Automate and optimize performance in Redshift environments
- Interactive Demo 5: Resize clusters from dc2.large to ra3.xlplus
- Implement best practices for securing your Redshift cluster
- Monitor cluster performance and troubleshoot issues effectively
- Review real-world data warehouse scenarios
- Activity: Design a modern analytics workflow using Redshift
- Examine patterns for building modern data architectures on AWS
- Understand how Redshift fits into broader analytics and data lake ecosystems
- Explore how Redshift integrates with machine learning tools like Amazon SageMaker for predictive insights
Who it's for
Data engineers, BI developers and analysts.
Before you start
- Students with a minimum one-year experience managing data warehouses will benefit from this course.
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