High flexibility and can be customized according to business needs. Disadvantages: High design complexity. Design principles of data warehouse Topic orientation: Data warehouse is oriented to specific business topics. Integration: Integrate data from different sources into a unified view. Time-varying: Data in the data warehouse changes over time. Non-volatility: Once data enters the data warehouse, it will not be modified or deleted.
Topic-oriented aggregation: Data in the data warehouse is Email List aggregated and aggregated according to topics. Data warehouse construction process Requirement analysis: Determine business requirements and clarify the goals of the data warehouse. Conceptual model design: Establish a conceptual model of the data warehouse and define business entities and attributes. Logical model design: Convert the conceptual model into a logical model and determine the table structure and relationship.
Physical model design: Convert the logical model into a physical model and determine the storage method and index. Data loading: Load data from the source system to the data warehouse. Metadata management: Establish a metadata management system to describe all data objects in the data warehouse. Application of data warehouse Decision support: Provide data support to management to help them make better decisions. Business analysis: Analyze business data to discover business trends and rules.