Overview
Learn how to use Amazon Redshift to create and manage data analytics pipelines through hands-on training.
Constructing Data Analytics Solutions The data analytics solution for the Using Amazon Redshift course includes an Amazon Redshift data warehouse. The analytics pipeline's components for data collection, ingestion, categorization, storing, and processing will all be covered. For use cases including data warehousing, you will plan and implement data analytics solutions. You will discover how to incorporate a data warehouse into a contemporary data architecture or data lake. You will also learn how to assist Amazon Redshift's security, performance, and cost optimization by using best practices during this session.
Those interested in pursuing a career in data lake development on AWS are welcome to enroll in the course.
- Compare the features and benefits of data warehouses, data lakes, and modern data architectures
- Design and implement a data warehouse analytics solution
- Identify and apply appropriate techniques, including compression, to optimize data storage
- Select and deploy appropriate options to ingest, transform, and store data
- Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case
- Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
- Secure data at rest and in transit
- Monitor analytics workloads to identify and remediate problems
- Apply cost management best practices
- Data Engineer
- Data Analyst
Required
- Students familiar with combining AWS technologies to support data lakes or other data-driven workloads will benefit from this course
Recommended
- Completed Building Data Lakes on AWS
- Completed either AWS Technical Essentials or Architecting on AWS