In this course, participants learn about the best practices for implementing an enterprise data warehouse. Participants identify the hardware elements that influence the throughput and learn how to build a balanced hardware configuration. Participants also review the two classic models: Third normal form (3NF) and star schema and learn how to optimize both models. Participants learn how to convert the logical model into a suitable physical model. Participants also learn how to load data efficiently into the data warehouse and how to use partition exchange load and data compression during the ETL process to improve performance. Finally, participants learn to manage the system workload and resources, to ensure an Enterprise Data Warehouse can run at optimal performance, and explains how parallel execution enables them to fully utilize the system. In addition, participants describe how to gather statistics efficiently.
Learn To:
- Describe how to build a balanced hardware configuration
- Discuss and apply the two classic models, the third normal form (3NF) or star schema
- Describe how to convert the logical model into the suitable physical model
- Describe the various methods to load data efficiently into the data warehouse
- Use partition exchange load and data compression during staging to improve performance
- Manage the system workload and resources
A Live Virtual Class (LVC) is exclusively for registered students; unregistered individuals may not view an LVC at any time. Registered students must view the class from the country listed in the registration form. Unauthorized recording, copying, or transmission of LVC content may not be made.