Course Description
Explore the fundamentals of data warehousing and the essential architectures and components being implemented to manage data.
Learning Objectives
Data Warehousing with Azure: Architecture & Modeling Techniques
- identify the essential characteristics of data warehouse and compare data warehouse with operational databases
- list the various possible data warehousing architectures that can be implemented
- recall the various essential data warehousing alternatives that are available today apart from Azure
- depict the evolution of data warehouse and illustrate the first generation and second generation data warehouse
- illustrate the various types of data warehouse that are being implemented by various businesses
- list the critical features of the federated data warehouse, compare federated data warehouse with the centralized approach, and list advantages and disadvantages of this approach and implementation scenarios
- identify the critical advantages and disadvantages associated with the star schema and data mart approaches of implementing data warehouse
- define the essential lifecycle phases of data warehousing implementation and data movement
- illustrate the essential concepts of metadata, types of metadata, and its roles in data warehouse implementation
- compare the essential approaches of processing, integrating, and managing structured and unstructured data
- compare the essential approaches of processing, integrating, and managing structured and unstructured data with real time examples
- specify the critical analytical and reporting mechanisms that are implemented in data warehouse
- define the benefits of implementing cloud data warehouse and compare cloud data warehouse with on-prem implementation
- describe the benefits and how to implement Hybrid architectures using on-premise capabilities
- define the critical features, characteristics, and advantages of implementing Federated and Hybrid data warehouse