Chapter 2 Data Models 2017 Cengage Learning®. May not be scanned,

Chapter 2 Data Models 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use.

Learning Objectives In this chapter, you will learn: About data modeling and why data models are important About the basic data-modeling building blocks What business rules are and how they influence database design 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 2

Learning Objectives In this chapter, you will learn: How the major data models evolved About emerging alternative data models and the need they fulfill How data models can be classified by their level of abstraction 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 3

Data Modeling and Data Models Data modeling: Iterative and progressive process of creating a specific data model for a determined problem domain Data models: Simple representations of complex real-world data structures Useful for supporting a specific problem domain Model - Abstraction of a real-world object or event 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 4

Importance of Data Models Are a communication tool Give an overall view of the database Organize data for various users Are an abstraction for the creation of good database 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 5

Data Model Basic Building Blocks Entity: Unique and distinct object used to collect and store data Attribute: Characteristic of an entity Relationship: Describes an association among entities One-to-many (1:M) Many-to-many (M:N or M:M) One-to-one (1:1) Constraint: Set of rules to ensure data integrity 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 6

Business Rules Brief, precise, and unambiguous description of a policy, procedure, or principle Enable defining the basic building blocks Describe main and distinguishing characteristics of the data 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 7

Sources of Business Rules Company managers Policy makers Written documentation Department managers Direct interviews with end users 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 8

Reasons for Identifying and Documenting Business Rules Help standardize company’s view of data Communications tool between users and designers Allow designer to: Understand the nature, role, scope of data, and business processes Develop appropriate relationship participation rules and constraints Create an accurate data model 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 9

Translating Business Rules into Data Model Components Nouns translate into entities Verbs translate into relationships among entities Relationships are bidirectional 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? 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 10

Naming Conventions Entity names - Required to: Be descriptive of the objects in the business environment Use terminology that is familiar to the users Attribute name - Required to be descriptive of the data represented by the attribute Proper naming: Facilitates communication between parties Promotes self-documentation 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 11

Hierarchical and Network Models Hierarchical Models Developed to manage large amounts of data for complex manufacturing projects Represented by an upsidedown tree which contains segments (equivalent of a file system’s record type) Depicts a set of one-to-many (1:M) relationships Network Models Created to represent complex data relationships effectively Improved database performance and imposed a database standard Allows a record to have more than one parent Depicts both one-to-many (1:M) and many-to-many (M:N) relationships 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 12

Standard Database Concepts Schema Conceptual organization of the entire database as viewed by the database administrator Subschema Portion of the database seen by the application programs that produce the desired information from the data within the database 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 13

Standard Database Concepts Data manipulation language (DML) Environment in which data can be managed and is used to work with the data in the database Schema data definition language (DDL) Enables the database administrator to define the schema components 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 14

The Relational Model Produced an automatic transmission database that replaced standard transmission databases Based on a relation Relation or table: Matrix composed of intersecting tuple and attribute Tuple: Rows Attribute: Columns Describes a precise set of data manipulation constructs 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 15

Relational Database Management System (RDBMS) Performs basic functions provided by the hierarchical and network DBMS systems Makes the relational data model easier to understand and implement Hides the complexities of the relational model from the user 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 16

Figure 2.2 - A Relational Diagram 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 17

SQL-Based Relational Database Application End-user interface Allows end user to interact with the data Collection of tables stored in the database Each table is independent from another Rows in different tables are related based on common values in common attributes SQL engine Executes all queries 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 18

The Entity Relationship Model Graphical representation of entities and their relationships in a database structure Entity relationship diagram (ERD) Uses graphic representations to model database components Entity instance or entity occurrence Rows in the relational table Connectivity: Term used to label the relationship types 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 19

Figure 2.3 - The ER Model Notations 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 20

The Object-Oriented Data Model (OODM) or Semantic Data Model Object-oriented database management system(OODBMS) Based on OODM Object: Contains data and their relationships with operations that are performed on it Basic building block for autonomous structures Abstraction of real-world entity Attributes - Describe the properties of an object 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 21

The Object-Oriented Data Model (OODM) Class: Collection of similar objects with shared structure and behavior organized in a class hierarchy Class hierarchy: Resembles an upside-down tree in which each class has only one parent Inheritance: Object inherits methods and attributes of parent class Unified Modeling Language (UML) Describes sets of diagrams and symbols to graphically model a system 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 22

Figure 2.4 - A Comparison of OO, UML and ER Models 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 23

Object/Relational and XML Extended relational data model (ERDM) Supports OO features and complex data representation Object/Relational Database Management System (O/R DBMS) Based on ERDM, focuses on better data management Extensible Markup Language (XML) Manages unstructured data for efficient and effective exchange of all data types 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 24

Big Data Aims to: Find new and better ways to manage large amounts of web and sensor-generated data Provide high performance and scalability at a reasonable cost Characteristics Volume Velocity Variety 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 25

Big Data Challenges Volume does not allow the usage of conventional structures Expensive OLAP tools proved inconsistent dealing with unstructured data 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 26

Big Data New Technologies Hadoop Hadoop Distributed File System (HDFS) MapReduce NoSQL 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 27

NoSQL Databases Not based on the relational model Support distributed database architectures Provide high scalability, high availability, and fault tolerance Support large amounts of sparse data Geared toward performance rather than transaction consistency Store data in key-value stores 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 28

Figure 2.5 - A Simple Key-Value Representation 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 29

Figure 2.6 - The Evolution of Data Models 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 30

Hierarchical Model Advantages Promotes data sharing Parent/child relationship promotes conceptual simplicity and data integrity Database security is provided and enforced by DBMS Efficient with 1:M relationships Disadvantages Requires knowledge of physical data storage characteristics Navigational system requires knowledge of hierarchical path Changes in structure require changes in all application programs Implementation limitations No data definition Lack of standards 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 31

Network Model Advantages Conceptual simplicity Handles more relationship types Data access is flexible Data owner/member relationship promotes data integrity Conformance to standards Includes data definition language (DDL) and data manipulation language (DML) Disadvantages System complexity limits efficiency Navigational system yields complex implementation, application development, and management Structural changes require changes in all application programs 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 32

Relational Model Advantages Disadvantages Structural independence is promoted using independent tables Tabular view improves conceptual simplicity Ad hoc query capability is based on SQL Isolates the end user from physical-level details Improves implementation and management simplicity Requires substantial hardware and system software overhead Conceptual simplicity gives untrained people the tools to use a good system poorly May promote information problems 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 33

Entity Relationship Model Advantages Visual modeling yields conceptual simplicity Visual representation makes it an effective communication tool Is integrated with the dominant relational model Disadvantages Limited constraint representation Limited relationship representation No data manipulation language Loss of information content occurs when attributes are removed from entities to avoid crowded displays 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 34

Object-Oriented Model Advantages Disadvantages Semantic content is added Visual representation includes semantic content Inheritance promotes data integrity Slow development of standards caused vendors to supply their own enhancements Compromised widely accepted standard Complex navigational system Learning curve is steep High system overhead slows transactions 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 35

NoSQL Advantages High scalability, availability, and fault tolerance are provided Uses low-cost commodity hardware Supports Big Data Key-value model improves storage efficiency Disadvantages Complex programming is required There is no relationship support There is no transaction integrity support In terms of data consistency, it provides an eventually consistent model 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 36

Table 2.3 - Data Model Basic Terminology Comparison 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 37

Figure 2.7 - Data Abstraction Levels 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 38

The External Model End users’ view of the data environment ER diagrams are used to represent the external views External schema: Specific representation of an external view 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 39

Figure 2.8 - External Models For Tiny College 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 40

The Conceptual Model Represents a global view of the entire database by the entire organization Conceptual schema: Basis for the identification and high-level description of the main data objects Has a macro-level view of data environment Is software and hardware independent Logical design: Task of creating a conceptual data model 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 41

Figure 2.9 - Conceptual Model For Tiny College 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 42

The Internal Model Representing database as seen by the DBMS mapping conceptual model to the DBMS Internal schema: Specific representation of an internal model Uses the database constructs supported by the chosen database Is software dependent and hardware independent Logical independence: Changing internal model without affecting the conceptual model 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 43

Figure 2.10 - Internal Model for Tiny College 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 44

The Physical Model Operates at lowest level of abstraction Describes the way data are saved on storage media such as disks or tapes Requires the definition of physical storage and data access methods Relational model aimed at logical level Does not require physical-level details Physical independence: Changes in physical model do not affect internal model 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 45

Table 2.4 - Levels of Data Abstraction 2017 Cengage Learning . May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part, except for use as permitted in a license distributed with a certain product or service or otherwise on a password-protected website or school-approved learning management system for classroom use. 46