{"id":1009,"date":"2025-01-12T20:57:19","date_gmt":"2025-01-13T01:57:19","guid":{"rendered":"https:\/\/pressbooks.bccampus.ca\/nelson\/chapter\/chapter-4-data-modelling-data-modeling\/"},"modified":"2025-01-12T21:02:28","modified_gmt":"2025-01-13T02:02:28","slug":"chapter04thirdedition","status":"publish","type":"chapter","link":"https:\/\/pressbooks.bccampus.ca\/nelson\/chapter\/chapter04thirdedition\/","title":{"raw":"Chapter 4 Data Modelling (Data Modeling)","rendered":"Chapter 4 Data Modelling (Data Modeling)"},"content":{"raw":"
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Original Chapter 4 Author: Adrienne Watt and Nelson Eng<\/p>\r\n

Original Chapter 5 Author: Adrienne Watt<\/p>\r\n

Rewrite: Fred Strickland<\/p>\r\n\r\n

Learning Outcomes<\/h2>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
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Computing Sub Discipline<\/strong><\/p>\r\n<\/td>\r\n

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Document <\/strong>C<\/strong>ode, Reference Code, and Page Number<\/strong><\/p>\r\n<\/td>\r\n

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Text<\/strong><\/p>\r\n<\/td>\r\n<\/tr>\r\n

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Computer Science<\/p>\r\n<\/td>\r\n

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CS2013<\/p>\r\n

IM\/Relational Databases (RD)<\/p>\r\n

(Page 115-116)<\/p>\r\n<\/td>\r\n

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1. Prepare a relational schema from a conceptual model developed using the entity- relationship model. [Usage]<\/p>\r\n<\/td>\r\n<\/tr>\r\n

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CS2023<\/p>\r\n

DM Modeling: Data Modeling<\/p>\r\n

(Pages 116-117)<\/p>\r\n<\/td>\r\n

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CS Core 1. Data modeling<\/p>\r\n

CS Core 2. Relational data model<\/p>\r\n

KA Core 3. Conceptual models (e.g., entity-relationship, UML diagrams).<\/p>\r\n

ILO KA Core 4. Model a given environment using a conceptual data model.<\/p>\r\n<\/td>\r\n<\/tr>\r\n

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CS2023<\/p>\r\n

DM-NoSQL: NoSQL Systems<\/p>\r\n

(Pages 120-121)<\/p>\r\n<\/td>\r\n

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KA Core 1. Why NoSQL? (e.g., Impedance mismatch between Application [CRUD] and RDBMS)<\/p>\r\n

ILO KA Core 1. Develop a use case for the use of NoSQL over RDBMS<\/p>\r\n<\/td>\r\n<\/tr>\r\n

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Information Systems<\/p>\r\n<\/td>\r\n

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IS2020<\/p>\r\n

A3.2 Data \/ Information Competency Realm<\/p>\r\n

(Page 101)<\/p>\r\n

A3.2.1 Competency Area \u2013 Data \/ Information Management<\/p>\r\n

(Page 101)<\/p>\r\n<\/td>\r\n

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2. Design relational databases (Page 103)<\/p>\r\n<\/td>\r\n<\/tr>\r\n

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Information Technology<\/p>\r\n<\/td>\r\n

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IT2017<\/p>\r\n

ITE-IMA-03 Data modeling<\/p>\r\n

(Page 92)<\/p>\r\n<\/td>\r\n

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b. Describe the relationship between a logical model and a physical model.<\/p>\r\n<\/td>\r\n<\/tr>\r\n

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Introduction to Chapter 4<\/h2>\r\n

The second edition Chapter 4 was a short chapter that explored at a high level the types of data models. The second edition Chapter 5 explored data modelling. For the third edition, these two chapters have been combined.<\/p>\r\n\r\n

Why Use a Model or a Framework?<\/h2>\r\n

We humans need something to help us to see the big picture. We could use a model or we could use a framework.<\/p>\r\n

A model <\/em>is a simplified representation of a system or of a process. It is a tool for breaking the complex into smaller and more manageable parts. Models can be used to help us to understand how something works. It could help us to predict how something might behavior in the future. A good example would be the Open Systems Interconnection (OSI) model, which is used to explain how computers communicate over a network.<\/p>\r\n

A framework<\/em> is a more structured approach for solving a problem. The framework may have a set of guidelines or rules for completing a task. Software engineers have the waterfall approach and the numerous agile approaches. The United States National Institute of Standards and Technology (NIST) has a cybersecurity framework that industry, government, and other organizations may use for reducing their cybersecurity risks. (See https:\/\/nvlpubs.nist.gov\/nistpubs\/CSWP\/NIST.CSWP.29.pdf<\/span><\/a>)<\/p>\r\n

A data model<\/em> provides a tool for communicating among stakeholders. It helps to understand what is important, what are the business rules, and what is the approach for implementing these items. Reviewing the models will reveal missing pieces and will help to correct errors.<\/p>\r\n

There are trade-offs for using data models. It takes a long time. As a result, there is the temptation or push to jump from one model to the next model. This is especially true for the concept model. And there is the temptation of adding pieces early to the diagrams. Experts fall into this trap by adding line notations. In the concept data model figures, ignore the extra markings.<\/p>\r\n\r\n

What Are the Models Used for Creating Databases?<\/h2>\r\n

In Chapter 2, we explored six database models. In this chapter, we will look at the data models for going from a concept to a fully working database management system (DBMS). We will look at the concept data model, the logical data model, and the physical data model.<\/p>\r\n\r\n

The Concept Data Model -- The \u201cWhat\u201d Model<\/h3>\r\n

We are at a high level. We are collecting data. Our great interest should be on the nouns and later the verbs. Look at the \u201cRunning Project\u201d at the end of Chapter 2. There is a list of entities<\/em> or objects.<\/p>\r\n

Once you have a good understanding of the nouns, then you can start to look at the relationship between the objects. Figure 4.1 shows a conceptual diagram that contains travel routes with associated schedules and airlines.<\/p>\r\n

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Figure 4.1 An example of a conceptual data model diagram. Source of image: https:\/\/www.couchbase.com\/blog\/conceptual-physical-logical-data-models\/<\/p>\r\n

Notice that we are not considering the data types. We are not considering how the data would be stored. We are not thinking about relationships. (Ignore the extra lines at the \u201cAirline\u201d box and at the \u201cSchedule\u201d box. We will address this topic elsewhere.) At this point, you could be thinking about a pile of papers on your desk or about a spreadsheet or about a database. At this point, you could be brainstorming on a whiteboard!<\/p>\r\n

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Figure 4.2 A large whiteboard. Source of image: https:\/\/www.magnatag.com\/img\/products\/WW\/WWcover1170-2.png<\/p>\r\n

Do spend a good amount of time in this model. Once the stakeholders have agreed that everything has been identified, then you can advance to the next model.<\/p>\r\n

Consider a database that has data on a school and on students. We will be focusing on entities and in time the relationships. In the relational DBMS approach, the term \u201cEntity-Relationship Diagrams<\/em>\u201d (ERDs) is used.<\/p>\r\n

We are interested in identifying the entities and the relationships. In an educational institution, we are looking at students, courses, instructors, and departments. For the relationships, we are looking at the following:<\/p>\r\n\r\n