Data Modeling 1 Yong Choi School of Business CSUB

Part # 2 2 Study Objectives Understand concepts of data modeling and its purpose Learn how relationships between entities are defined and refined, and how such relationships are incorporated into the database design process Learn how ERD components affect database design and implementation Learn how to interpret the modeling symbols

Part # 2 Data Model and Data Modeling Model: an abstraction of a real-world object or event Useful in understanding complexities of the real- world environment Data model Relatively simple representations of complex real- world data structures Data modeling is iterative and progressive process

Part # 2 Data Model by Access 4

Part # 2 Data Model by Peter Chen’ Notation (first - original)

Part # 2 6 Data modeling The data modeling revolves around discovering and analyzing organizational and users data requirements based on business rules. Identify what data is important Identify what data should be maintained The major activity of this phase is identifying entities, attributes, and their relationships to construct model using the Entity Relationship Diagram.

Part # 2 Data Model Basic Building Blocks Entity : anything about which data are to be collected and stored Attribute: a characteristic of an entity Relationship: describes an association among entities One-to-many (1:M) relationship Many-to-many (M:N or M:M) relationship One-to-one (1:1) relationship Constraint: a restriction placed on the data

Part # 2 The Importance of Data Model Blue print: documentation Facilitate interaction among the managers, the designer, and the end user Effective Communication Tool User involvement Independence from a particular DBMS

Part # 2 Business Rules Descriptions of policies, procedures, or principles within a specific organization Use for discovering and analyzing organizational and users data requirements for the data model Use for describing characteristics of data Allow designer to understand business processes Allow designer to develop appropriate relationship participation rules and constraints

Part # 2 Discovering Business Rules Sources of business rules: Top management (policy makers) and managers Written documentation Procedures Standards Operations manuals Direct interviews with end users

Part # 2 Translating Business Rules into Data Model Components Nouns translate into entities Verbs translate into relationships among entities Relationships are bidirectional Two questions to identify the relationship type: How many instances of B are related to one instance of A? How many instances of A are related to one instance of B? Example relationship between student and class: In how many classes can one student enroll? – many classes How many students can enroll in one class? – many students

Part # 2 Business Rules Example 1 A professor can teach many classes and each class is taught by one professor. A professor can advise many students and each student is advised by one professor. 12

Part # 2 Business Rules Example 2 Each sales representative writes many invoices and each invoice is written by one sales representative. Each sales representative is assigned to many department and each department has one at most one sales representative. Each customer can generate many invoices and each invoice is generated by one customer. 13

Part # 2 14 Entity Relationship diagram (ERD) Data modeling methodology Developed by Peter Chen (1976). Entity : anything about which data are to be collected and stored Attribute - property or characteristic of interest of an entity (a field in a table) Relationship – association between entities (corresponds to primary key-foreign key equivalencies in related tables)

Part # 2 15 Entity “A fundamental THING of relevance to the enterprise about which data may be kept” What should be an Entity: both tangible & intangible An object that will have many instances in the database An object that will be composed of multiple attributes An object that we are trying to model

Part # 2 16 Most popular ERD Notation (very minor differences with our textbook)

Part # 2 17 Entity Instance Entity instance: a single occurrence of an entity. 6 instances Student ID Last Name First Name 2144ArnoldBetty 3122TaylorJohn 3843SimmonsLisa 9844MacyBill 2837LeathHeather 2293WrenchTim Entity: student instance

Part # 2 18 Entity Instance (con’t)

Part # 2 Entity Type and Entity Instances 19

Part # 2 20 “Describe characteristics of an entity ” Entity: Employee Attributes: Employee-Name Address (composite) Phone Extension Date-Of-Hire Job-Skill-Code Salary Attributes

Part # 2 21 Classes of attributes Simple attribute Composite attribute Derived attributes Single-valued attribute Multi-valued attribute

Part # 2 22 A simple attribute cannot be subdivided. Examples: Age, Gender, and Marital status A composite attribute can be further subdivided to yield additional attributes. Examples: ADDRESS --  Street, City, State, Zip PHONE NUMBER --  Area code, Exchange number Simple/Composite attribute

Part # 2 23 is not physically stored within the database instead, it is derived by using an algorithm. Example: AGE can be derived from the date of birth and the current date. MS Access: int(Date() – Emp_Dob)/365) Derived attribute

Part # 2 24 can have only a single (atomic) value. Examples: A person can have only one social security number. A manufactured part can have only one serial number. A single-valued attribute is not necessarily a simple attribute. Part No: CA Location: CA, Factory#:08, shift#: 02, part#: Single-valued attribute

Part # 2 25 can have many values. Examples: A person may have several college degrees. A household may have several phones with different numbers A car color Multi-valued attributes

Part # 2 26 Example - “Movie Database” Entity: Movie Star Attributes: SS#: “ ” (single-valued) Cell Phone: “(661) , (661) ” (multi-valued) Name: “Harrison Ford” (composite) Address: “123 Main Str., LA, CA” (composite) Birthdate: “1-1-50” (simple) Age: 50 (derived)

Part # 2 27 How to find entities? Entity: A fundamental thing of relevance to the organization about which data may be kept people, places, objects, events…. Tangible: customer, product Intangible: order, invoice look for nouns (beginner) BUT a proper noun is not a good candidate….

Part # 2 28 How to find attributes? Attribute: property or characteristic of an entity A descriptor whose values are associated with individual entities of a specific entity type look for characteristics of entity

Part # 2 29 “ attributes that uniquely identify entity instances” Uniquely identify every instance of the entity One or more of the entity’s attributes Composite identifiers are identifiers that consist of two or more attributes Identifiers are represented by underlying the name of the attribute(s) Employee (Employee_ID), student (Student_ID ) (unique) Identifier

Part # 2 Practice Try Practice 1 – 4 from Data Modeling Practice slide from week 6 – class website. 30