Business Rules and Data Models
Student’s name
Professor’s name,
Course title,
Date
A database is filing system and an application used to collect, organize and store information for various reasons such as to have a huge amount of information for future use, to computerize a computer procedure of some classification according to the stored data and for quick search ability. Databases determine the information displayed on websites, to keep fiscal records, to record computer files as well as to maintain one’s in- box. Colleges use huge amounts of different data that need to be classified and stored for their references in academic work. On the other side, data base is crucial to keep track of the instructors, their subjects and the courses they teach (Kroenke, 2006).
An entity is an object that has a physical existence or conceptual existence such as; a place a person, a university course, a thing, a person, a job or a company that data can be collected.
For instance to develop a college’s database for maintaining information on students, the application should be able to provide and store data on students such as when was the student was admitted; is the student still with the college; if the student has left the college when did he leave the college; which course does the student partake; who is his/her instructor; what stage the student is in and much more. In the above example, the entities are college, course, student, and instructor. The entities that are being tracked are stored in database tables that have table rows and their names on the row box (Kanchinadam, 2008).
Attributes
An Attribute is a property that makes up an entity thus Databases have information on each entity that is tracked in character fields known as attributes. This usually corresponds to the data base table columns. For instance, the student’s entity might have attributes corresponding to the student’s first and last name, date of birth, and a unique student identifier such as the admission number.
Business rules are the rules a company or firm uses to define its constraints. They assert the manner in which the business is controlled or influenced. The rules apply to individuals, corporate behavior and the organization of the firm’s computing systems in order to achieve the organizational set goals. The art of writing down business rules ensures that incidences where conflicts occur because of poor interpretation of rules are limited and it is also cost effective.
There are several business rules; For instance, the facts relating relevant terms to each other rule is used to illustrate how a language can be expressed. In this case, a customer’s decision to place a business order acts as a business rule. The facts that have been documented by the customer can act as relationships and also as attributes in creating graphical models.
The description of business terms is mainly the basic business rule. It is used to provide a description of the manner in which individuals think and discuss about things. Terms are documented in the glossary and can be utilized in creating conceptual models. Conceptual data models are used in the structuring of strategic data models. The model posses an abstract nature hence referred to as the conceptual models. The model has a varying number of entities between 100-1000 entities though they are dependent on the model’s scope. Often, in the conceptual model, the attributes have data types that are assigned with both length and precision. The model too addresses in two dimensions majorly the cardinality and null ability (Kanchinadam, 2008).
On the other hand, physical models use objects including columns and tables that are generated on the basis attributes and entities that were identified in logical modeling. The physical model is software data specific. Their constraints may include foreign keys, check constraints as well as primary keys (Kanchinadam, 2008).
References
Kroenke, D. M. (2006). Database processing: fundamentals, design, and implementation (10th
ed.). Upper Saddle River, N.J.: Pearson Prentice Hall.
Kanchinadam, K. M. (2008). DataMapX a tool for cross-mapping entities and attributes between
bioinformatics databases. Fairfax, VA: George Mason University.
