• Unit 3: Data Models

    In Unit 2, you learned that database design is a process to facilitate the construction, development, implementation, and maintenance of database management systems. Unit 3 will add to your knowledge of database design. This unit introduces data models. Your ability to understand and explain data models is the first step to designing a database. Data models are abstract models that organize data elements and define the logical inter-relationships between different data elements. The purpose of data models is to represent "what data are required" and "what format to use" in business practices. Data models facilitate organizational communication and development. Therefore, data models are used to accurately represent requirements by designing responses needed to answer those requirements.

    Completing this unit should take you approximately 8 hours.

    • 3.1: Types of Data Models

      The primary role of data models is to determine how data is revealed to the end user. Data professionals create and structure database tables to answer specific business questions. Data models ensure the best possible data analysis by revealing the most relevant data requested by the end user. Remember, data modeling is NOT data analysis. Data modeling optimizes the process in order to deliver clean and usable data for analysis.

      • 3.1.1: Conceptual Models

        A conceptual model focuses on identifying data used within a business. It is used to support business development, events, and track performance measures. However, it does not focus on process flow or other physical characteristics.

      • 3.1.2: Logical Models

        Logical data models are a way to translate business concepts for data purposes/uses into Entity-Relationship diagrams. Logical data models describe data in as much detail as possible. This model is more complex than conceptual models. Logical data models establish column (data) types to include all entities and relationships among them. Remember, logical data models have nothing to do with creating a database. Identifying the data elements we want to translate and identifying how they are related through key fields.

      • 3.1.3: Physical Models

        Physical data models define all required logical database components and services to build a database. Physical data models can also be a layout of an existing database. Normally, physical data models contain the table structure, column names, primary keys, and other relationships among tables. The most commonly used physical model is the Relational Model. The relational model was originally developed by Edgar F. Codd in 1969 and has become the international standard. Today most Database Management Systems are Relational Database Management Systems (RDBMS). Gaining an understanding of the relational model and relational databases is thus a key skill for anyone seeking to work in the data management field.

    • 3.2: Data Model Advantages and Disadvantages

      Data models are critical in producing higher-quality data, faster performance, and few data errors. However, as a data professional, it is important to be able to explain the advantages and disadvantages of data models. We can construct data models using a number of techniques. The Entity-Relationship (E-R) model is in wide use. In addition to being an effective modeling technique in and of itself, E-R modeling also facilitates the easy construction of a relational model for implementation in a relational database management system (RDBMS). Note the role of E-R modeling as you proceed through this lesson.

    • 3.3: The Enhanced E-R Model and Business Rules

      An entity-relationship (E-R) model is also known as an entity-relationship (E-R) diagram. An E-R model is a graphical representation of entities and their relationship with each other. E-R models are usually applied with organizing data within databases and information systems.

      Business rules describe organizational policies that apply to the data stored in a database. Business rules contain two constraints. (1) Field constraints within tables and (2) relationship constraints between two or more tables. Therefore, business rules reflect how an organization understands the use of its data.

      • 3.3.1: Supertypes and Subtypes

        Supertypes and subtypes happen frequently in the business world. An entity is known as a supertype. Each group established within the entity is known as a subtype. An entity subtype contains unique characteristics of the subtype. For example, an employee is a "supertype" and a professor is a "subtype" of an employee.

      • 3.3.2: How Business Rules are Used

        Business rules are intended for organizations that use data to explain policy, procedure, or principles. Business rules define entities, attributes, relationships, and constraints.

    • 3.4: Database Security

      Data represents a critical asset for organizations. Any valuable asset can attract the interest of people who wish to steal the asset or harm the organization controlling the asset. For this reason, database security is a critical function of any database system. We need to ensure that only those people with a legitimate need to access the data are granted permission to access the data.

    • Study Guide: Unit 3

      We recommend reviewing this Study Guide before taking the Unit 3 Assessment.

    • Unit 3 Assessment

      • Receive a grade