- Course overview
- Course details
- Prerequisites
Course overview
About this course
This course is designed to equip learners with the expertise to leverage Amazon Redshift for Data warehousing and analytics. This course covers a range of topics from data analytics use cases to the intricate details of Amazon Redshift's Architecture, features, and management practices. As learners progress through the course, they'll explore how Amazon Redshift fits into the data analytics pipeline, learning about Ingestion, Storage, Processing, Optimization, and Security.
Audience profile
This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines.
Course details
Module A: Overview of Data Analytics and the Data Pipeline
• Data analytics use cases
• Using the data pipeline for analytics
Module 1: Using Amazon Redshift in the Data Analytics Pipeline
• Why Amazon Redshift for data warehousing?
• Overview of Amazon Redshift
Module 2: Introduction to Amazon Redshift
• Amazon Redshift architecture
• Interactive Demo 1: Touring the Amazon Redshift console
• Amazon Redshift features
• Practice Lab 1: Load and query data in an Amazon Redshift cluster
Module 3: Ingestion and Storage
• Ingestion
• Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API
• Data distribution and storage
• Interactive Demo 3: Analyzing semi-structured data using the SUPER data type
• Querying data in Amazon Redshift
• Practice Lab 2: Data analytics using Amazon Redshift Spectrum
Module 4: Processing and Optimizing Data
• Data transformation
• Advanced querying
• Practice Lab 3: Data transformation and querying in Amazon Redshift
• Resource management
• Interactive Demo 4: Applying mixed workload management on Amazon Redshift
• Automation and optimization
• Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster
Module 5: Security and Monitoring of Amazon Redshift Clusters
• Securing the Amazon Redshift cluster
• Monitoring and troubleshooting Amazon Redshift clusters
Module 6: Designing Data Warehouse Analytics Solutions
• Data warehouse use case review
• Activity: Designing a data warehouse analytics workflow
Module B: Developing Modern Data Architectures on AWS
• Modern data architectures
Prerequisites
- Basic understanding of data warehousing concepts
- Familiarity with SQL
- Awareness of cloud computing basics
- Experience with data analytics concepts
- General IT knowledge
Enquiry
Course : Building Data Analytics Solutions Using Amazon Redshift
Enquiry
request for : Building Data Analytics Solutions Using Amazon Redshift
