Data modeling refers to methods in computer science for the formal mapping of relevant context objects by their attributes and relationships. The main objective is the clear definition and specification of the managed objects in an information system as part of Component Analysis.
Only attributes and the relationships between information objects are required for informational purposes in order to obtain an overview of the data view of the information system. Data modeling can also be used outside of projects for application development.
Data models have a normally much longer life than the functions and processes of software. The rule is: “Data is stable – functions are not”. Data can continue to be used when software is replaced.
The data modeling, as an essential part of the discipline of software development proceeds through different phases. The activities are created procedurally, that is, they identify goals or purposes, activities and results, building on each other, carry on intermediate to ultimately final Component Analysis results.
In terms of specific milestones in the project arise the following model variants: Conceptual database schema: Starting from the observation of a section of the real world, the relevant properties and relationships between them are collected, analyzed and formulated graphically and textually.
Logical Database Schema: The conceptual database schema is mapped to a logical database schema. Here, the model is extended with technical data (eg field formats, identifying keywords, etc.). The logical database schema obeys the rules given by the DBMS structure to be used, for instance, the relational data model, in which all data is stored in Component Analysis tables.
Physical database schema: To implement the data model with a specific database system (DBMS) all information on the syntax of the DBMS must be formulated for database generation. In part, this is automatically or semi-automatically possible with the use of Component Analysis generators.
With these three levels of the model and the procedure, only one basic approach is outlined. In detail this approach, the (intermediate) results and also the names of the models of the frequently used company-specific process models and of the used modeling methodology and software are determined. When using the DBMS as a modeling tool, the model boundaries are blurred, and the models evolve gradually to the final database. In data modeling, data is not generally included, belonging to the technical and substantive purpose of the systems.
Data validation in software engineering refers to the examination of the inputs from the user or external data sources. Because missing or unusable entries can lead to failure of the program, these values must be validated.