Data Warehousing Special Topic (6)-Data Warehouse, subject domain, topic concept and definition

First, the Data Warehouse

The standard definition of the Data Warehouse concept is relatively high in the industry, as proposed by Bill Inmon, the father of the Data Warehouse, in the book "Building The Data Warehouse" (Bill Enmen), published in 1991:

Chinese definition: Data Warehouse is a subject-oriented, integrated, relatively stable, historical change of data collection, to support management decisions.

English definition: A data Warehouse is a subject-oriented, integrated, Nonvolatile, and time-variant collection of the data in the support of Nagement ' s decisions.

Second, the theme

The topic is corresponding to the application of the traditional database, is an abstract concept , is the abstraction that synthesizes, classifies and analyzes the data in Enterprise information system at a higher level. Each topic corresponds to a macro analysis area . In the logical sense, it is the analysis Object which is involved in a macro analysis field in the corresponding enterprise. The topic-oriented data organization method is a complete and consistent description of the analytical object data at a higher level, which can describe the enterprise data involved in each analysis object, as well as the connection between the data. The so-called higher level is relative to the application-oriented approach to data organization, refers to the way the data organized by the topic has a higher level of data abstraction. The data in the Data Warehouse is organized by the topic, which corresponds with the characteristic of the traditional database oriented to the application. The subject is determined according to the requirements of the analysis. This is different from organizing data according to data processing or application requirements.

Third, subject area

Subject fields are often a collection of closely related data topics . You can divide these data topics into different subject fields based on your business concerns. The determination of the subject domain must be done jointly by the end user and the designer of the Data Warehouse .

Iv. topic domains, themes, inter-entity relationships

Theme design is the process of further decomposition and refinement of the subject domain. Subject fields can have more than one theme, and themes can be divided into more sub-themes, while entities are the smallest units that cannot be divided. The relationship of subject fields, themes, and entities is as follows:

V. Controversy over the subject area

You've seen another way to define a topic field: "The Subject field is the boundary of the subject that is determined after the analysis of a topic." The relevant content is as follows:

A subject field is the boundary of a topic that is determined after an analysis of a topic. The first step in information packaging technology is to analyze the topic domain and determine the topic to mount to the Data warehouse. When designing a data warehouse, it is generally a matter of creating a topic or a part of the enterprise's entire topic at a time, so that in most data warehouse design process There is a topic domain selection process. the determination of the subject domain must be done jointly by the end user and the designer of the Data Warehouse .

For example, for adventure Works cycle This type of company management needs to analyze topics that typically include vendor topics, product topics, customer topics, and warehouse topics. Among them, the content of the subject includes recording the purchasing situation of the supermarket goods, the sale of the goods and the storage of the goods; Customer topics include content that customers may purchase, and warehouse topics include storage of goods in warehouses and management of warehouses, as shown in 3-31.

Figure 3-31 Analysis topics determined by business conditions

Determining the subject boundary actually requires a further understanding of the business relationship, so after you determine the entire analysis topic, you need to make a preliminary elaboration of these topics to facilitate access to the boundaries that each topic should have. For the 4 topics in Figure 3-31 and their business relationships in the enterprise, it is possible to identify boundary 3-32 as shown.

Figure 3-32 Dividing the subject field

In-depth analysis of the above content, found that this definition and: "Subject field is usually a more closely linked collection of data Themes " is not contradictory, but the perspective of the station is different, "Data theme Collection" View from the data, the premise is that has been analyzed, Comb the list of all possible data topics, where the subject of the data is fine-grained, from microscopic to macroscopic; in the perspective of "Frontier theory", a topic is a topic of analysis, a macro concept, not a data subject.

Vi. continuation of the non-completion

Distributed Data Warehouse data storage model design, follow-up will continue to update, please pay attention to QQ Group: Distributed Data Warehouse modeling 398419457.

Data Warehousing Special Topic (6)-Data Warehouse, subject domain, topic concept and definition