What are the contents of data warehouse implementation?

Daily business involves frequent and simple data access, so the performance requirements for operation and processing are relatively high, and the database needs to be able to respond in a short time.

2. Data integration

The operation and processing of enterprises are usually decentralized, and the application-oriented characteristics of traditional databases make data integration difficult.

3. Data update

Operation processing is mainly composed of atomic transactions, and data is frequently updated, which requires parallel control and recovery mechanism.

4. Time limit of data

Operation processing mainly serves daily business operations.

5. Data synthesis

Operating processing systems usually have only simple statistical functions.

Databases have been widely used in the field of information technology, and almost all departments in our social life have various databases to store all kinds of data closely related to our lives. As a branch of database, the concept of data warehouse is put forward, which is much closer to the database in time. Dr. WilliamInmON, a famous American information engineering expert, put forward the concept of data warehouse in the early 1990s. He said: "Data warehouse is usually a subject-oriented, integrated and time-varying data set, but the information itself is relatively stable and used to support the management decision-making process."

The theme here refers to the key aspects that users care about when making decisions using data warehouse, such as revenue, customers, sales channels, etc. Topic-oriented means that the information in the data warehouse is organized by topic, not by business function like business support system.

Integration means that the information in the data warehouse is not simply extracted from various business systems, but through a series of processes of processing, sorting and summarizing, so the information in the data warehouse is consistent global information about the whole enterprise.

Changing with time means that the information in the data warehouse not only reflects the current state of the enterprise, but also records the information from a certain point in the past to the current stages.