Data Models in Databases

I learned database (3) -- Data Models in the database this essay and essay (4), essay (5) and essay (6) I have a detailed understanding of the data model. As this is the core and foundation of the database system, I must have a clear understanding of the data model, data Models are abstracted, so there are some concepts here.

I learned database (3) -- Data Models in the database this essay and essay (4), essay (5) and essay (6) I have a detailed understanding of the data model. As this is the core and foundation of the database system, I must have a clear understanding of the data model, data Models are abstracted, so there are some concepts here.

I learned database (3) -- Data Model in the database

This essay and essay (4), essay (5), and essay (6) mainly provide a detailed understanding of the data model, because this is the core and basis of the database system, therefore, you must have a clear understanding of the data model. The data model is abstracted. Therefore, there are some concepts that may be hard to understand, but there is no way to understand them, if you want to learn this "art", you must understand this and have a profound understanding. Let's just move on to the subject and start learning the data model, fighting!

Data Model: data and model. Therefore, you must first understand these two terms.

Data is a physical symbol that records information in a regular arrangement. It can be numbers, text, images, or computer code. Receiving information begins with receiving data. Obtaining information can only be interpreted as a data background.

Models, such as aircraft models, are no longer familiar to us. Because we have seen real things. A model is a simulation and abstraction of the characteristics of an object in the real world. It is a representation system used to analyze the concepts, mathematical relationships, logical relationships, and algorithm sequences of problems.

To sum up, the Data Model is the abstraction of Data features, used to analyze the concept of Data problems and the representation system of various relations between Data. That is to say, it is used to describe data, organize data, and operate on data. Selecting a data model is not so casual. You cannot abstract a data and use it as a model. The data model must meet certain requirements: first, it can simulate the real world in a more realistic way. Here we use the comparison term to describe it because the model is a model and cannot completely simulate the world. Instead, it is easy to understand, obscure, it will lose the abstract meaning. Third, it is easy to implement on the computer. I understand this condition. If we want the human brain to implement it, i'm afraid it must be like Einstein or hawking. After all, the human brain is restricted. Computers at this level are much better than the human brain. But the problem arises again. What data model can fully meet these three conditions? The answer is that there are no data models in this region. Therefore, different data models must be used for different objects and applications. This is also done in the database system, that is, different data models are used at different stages of the development and implementation of the database application system: Conceptual Models, logical models, and physical models. In fact, we first describe what it is, then how it is represented, and finally how it is implemented. To put it bluntly, it is the process of discovering problems, Hong Kong Space, analyzing and solving problems.

Conceptual Data Models, also known as information models, are used to describe the conceptual structure of the world for database users, it enables database designers to get rid of the technical problems of computer systems and DBMS in the initial stage of design, and focus on analyzing data and the relationship between data, which is irrelevant to the specific DBMS. This model is designed to meet the real needs of the real world. The success or failure of the database application system is directly determined by the construction of this model.

The Logical Data Model is used in the process of representation. This is the data model that the user sees from the database. It is the data model supported by the specific DBMS, and the website space, for example, the mesh data model, hierarchical data model, relational model, object-oriented model, and object relational model. This model must be user-oriented and system-oriented. The reason for this is that the logic model is directly converted from the conceptual model, and further problems may occur during the conversion process, these problems need to be resolved to the conceptual model for further discussion. The reason for system-oriented, as we mentioned earlier, since it is a model, it will be easily implemented by computers, this model models data from the perspective of computer systems and is mainly used for DBMS implementation.

The physical data model is used in the implementation process. This is a data model that describes the organizational structure of data on the storage media. It is not only related to the specific DBMS, it is also related to the operating system and hardware. Each Logical Data Model has its own physical data model. To ensure its independence and portability, most of the implementation of physical data models is automatically completed by the system. Designers only design special structures such as indexing and clustering. This model is purely system-oriented and abstracts data from the computer perspective at the lowest level.

Next, let's take a look at the common characteristics of the data model. Generally, a data model is a set of strictly defined concepts. These concepts precisely describe the static features (data structure), dynamic features (data operations), and integrity constraints of the system. These are the three elements of the data model, that is, the commonality of the data model.

A Data Structure is a collection of object types. These objects are a part of the database. The data structure refers to the expression and implementation of the relationship between objects and the static features of the system. They include two aspects: one is about the data object itself, such as type, content, and nature. On the one hand, it refers to the connection between data, server space, and how data is interconnected.

Data operations are a set of operations that can be performed on instances of objects in the database. They mainly refer to operations such as search and update (insert, delete, and modify. The data model must define the exact meaning of these operations, Operation symbols, operation rules (such as priority), and language for implementing the operation. Data operations are a description of the system's dynamic features.

Data integrity constraints are a set of integrity rules that specify the conditions for database status and status changes to ensure data correctness, validity, and compatibility. I also mentioned why the file system cannot meet the requirements of increasing daily. One of the reasons is that the file system cannot provide integrity rule constraints, this is also the essential reason why the file system cannot ensure data correctness, validity, and consistency.

Next time, we will discuss the conceptual model in the data model.

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