logical model

Logical structure of data

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Logical model refers to the Logical structure 。 Logical modeling yes data warehouse An important link in implementation, because it can Direct reflection Out Business Department At the same time, it plays an important role in guiding the physical implementation of the system. Its role is to outline the data blueprint of the enterprise through entities and relationships.

Chinese name: logical model
Foreign name: the logic model

Explain in detail: It refers to the logical structure of data.
Pinyin: luó jí mó xíng
Contains: Relationship, network, hierarchy

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Development History

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In logical model hierarchical model and Mesh model It's early data model , collectively referred to as non relational model 。 From the 1970s to the early 1980s, the non relational model database system It is very popular, and accounts for leading role , has been gradually replaced by the relational model database system, but in the United States and other places, due to the early development of application system Are based on hierarchy or Mesh database System, so Hierarchical database There are still many network database systems.

Since the 1980s, object-oriented methods and technologies have been used in various computer fields, including Programming language ， software engineering , computer hardware and other aspects have had a profound impact, and a new model - object-oriented data model has emerged.

classification

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logical model

The most common logical models are hierarchical model , mesh model and relational model.

The fundamental difference between the three logical models lies in the different data structures, that is Expression Different, used for hierarchical model“ Tree structure ”To represent the relationship between data; Mesh model uses "graph structure" to represent the relationship between data; The relationship model uses“ 2D table ”To represent the relationship between data.^[1]

Three elements

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A logical model is a set of strictly defined concepts, mainly composed of data structure 、 Data operation and integrity constraint Part composition is usually called the three elements of data.

data structure

Data structure is computer data organization Framework description of the relationship between methods and data, and data file The data of is organized according to this framework description.

The data structure is described in object type The collection of is a static description of the system.

Data operation

Data operation refers to the set of operations allowed to be performed on instances or values of various objects in the database, including operation methods and relevant rules Dynamic characteristics Description of.

integrity constraint

Completeness A constraint is a set of integrity rules for data（ constraint condition ）Collection of. The logic logic shall reflect and specify the basic general integrity constraints that the data model must comply with. For example, in a relational model, any relationship must satisfy Entity integrity and Referential integrity Two conditions. In addition, the logical model should also provide a mechanism for user-defined integrity constraints to reflect the specific semantic constraints that data involved in specific applications must comply with.^[2]

Design steps

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Analysis subject field

In the conceptual model design, we have determined several basic subject areas, but, data warehouse The design method of Gradual refinement The process of design is generally completed one theme at a time or several themes at a time. Therefore, we must understand the concept model design Several identified in step Basic theme Domain analysis, and select the subject domain to be implemented first. When selecting the first topic domain, we should consider that it should be large enough so that the topic domain can be built into an applicable system; It should also be small enough to facilitate development and rapid implementation.

Granularity hierarchy division

data warehouse logic design An important problem to be solved in is to determine the granularity level of the data warehouse. Whether the granularity level is appropriate or not directly affects the amount of data in the data warehouse and the appropriate query type. because Subject database Respond to enterprise business OLTP Therefore, the most detailed classification data must be saved according to the Business Department In order to improve the speed of complex queries, multiple granularity should be determined.

Determine data segmentation strategy

In this step, choose the appropriate Data segmentation In general, the following factors should be considered: data volume (not the number of record lines) Data analysis The actual situation, simplicity and granularity division strategy of the processing. Among them, the size of the data is the main factor that determines whether to segment the data and how to segment it; The requirements of data analysis and processing are a main basis for selecting data segmentation standards, because data segmentation is closely related to the objects of data analysis and processing.

Relationship schema definition

Each topic of the data warehouse is realized by multiple tables, which are linked together by the public key of the topic to form a complete topic. When designing the conceptual model, we determined the basic theme of the data warehouse, and described the public key and basic content of each theme. In this step, we will divide the selected currently implemented topics into patterns, form multiple tables, and determine the Relational model 。

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