Data Warehousing on AWS
About This Course
Data is a critical asset for organisations supporting analytics, business intelligence and data-driven decision-making. Cloud data warehousing provides scalable platforms for integrating, storing, transforming and analysing data from multiple sources.
This 3-day course provides practical knowledge and hands-on experience in designing, implementing and managing a data warehouse using Amazon Redshift. Participants will explore modern data architecture, data modelling, data loading, SQL analysis, backup and recovery, performance tuning, security, orchestration, machine learning and data sharing.
Through demonstrations and hands-on AWS labs, participants will configure an Amazon Redshift data warehouse, load and analyse data, optimise performance, secure the environment, orchestrate data pipelines and apply Amazon Redshift ML. The course also introduces data sharing through Amazon Redshift and Amazon DataZone.
The course develops competencies in Data Engineering, Data Strategy and Data Design, enabling participants to make informed decisions about data warehouse architecture and implementation while applying AWS best practices for reliable, secure and scalable analytical data platforms.
What You'll Learn
● LO1 - Explain the role of Amazon Redshift in modern data architecture and identify appropriate data warehouse architectures, data models and data sources for analytical workloads.
● LO2 - Describe data management and data loading approaches in Amazon Redshift and apply appropriate ETL, ELT and data ingestion techniques for integrating data from Amazon S3, streaming sources and relational databases.
● LO3 - Design a cloud-based data warehouse solution using Amazon Redshift and configure data models, permissions and warehouse components according to data, business and operational requirements.
● LO4 - Implement data warehouse operations using Amazon Redshift and use SQL Query Editor v2, notebooks and AWS orchestration services to query, transform, analyse and automate data workflows.
● LO5 - Optimise Amazon Redshift data warehouse performance through query analysis, table maintenance, workload management and monitoring, and secure the data warehouse using appropriate authentication, access control, encryption, auditing and compliance practices.
● LO6 – Evaluate Amazon Redshift solutions based on reliability, performance, security, data sharing and business requirements, and apply appropriate backup and recovery, machine learning and data-sharing strategies to support organisational data needs.
Entry Requirements
• Familiarity with building and managing Data Lakes on AWS
• Familiary with Building Data Analytics Solutions Using Amazon Redshift