Database Systems Design Implementation and Management 10th Edition Chapter 2
Database Systems: Design, Implementation, and Management Tenth Edition Chapter 2 Data Models 1 Database Systems, 10 th Edition
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 How the major data models evolved 2 Database Systems, 10 th Edition
Objectives (cont'd. ) About emerging alternative data models and the need they fulfill How data models can be classified by their level of abstraction 3 Database Systems, 10 th Edition
Introduction Designers, programmers, and end users see data in different ways Different views of same data lead to designs that do not reflect organization's operation Data modeling reduces complexities of database design Various degrees of data abstraction help reconcile varying views of same data 4 Database Systems, 10 th Edition
Data Modeling and Data Models Data models Relatively simple representations of complex real-world data structures Often graphical Model: an abstraction of a real-world object or event Useful in understanding complexities of the real-world environment Data modeling is iterative and progressive 5 Database Systems, 10 th Edition
The Importance of Data Models Facilitate interaction among the designer, the applications programmer, and the end user End users have different views and needs for data Data model organizes data for various users Data model is an abstraction Cannot draw required data out of the data model 6 Database Systems, 10 th Edition
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 7 Database Systems, 10 th Edition
Business Rules Descriptions of policies, procedures, or principles within a specific organization Apply to any organization that stores and uses data to generate information Description of operations to create/enforce actions within an organization's environment Must be in writing and kept up to date Must be easy to understand widely disseminated Describe characteristics of data as viewed by the company 8 Database Systems, 10 th Edition
Discovering Business Rules Sources of business rules: Company managers Policy makers Department managers Written documentation Procedures Standards Operations manuals Direct interviews with end users 9 Database Systems, 10 th Edition
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? 10 Database Systems, 10 th Edition
Naming Conventions Naming occurs during translation of business rules to data model components Names should make the object unique and distinguishable from other objects Names should also be descriptive of objects in the environment and be familiar to users Proper naming: Facilitates communication between parties Promotes self-documentation 11 Database Systems, 10 th Edition
The Evolution of Data Models 12 Database Systems, 10 th Edition
The Relational Model Developed by E. F. Codd (IBM) in 1970 Table (relations) Matrix consisting of row/column intersections Each row in a relation is called a tuple Relational models were considered impractical in 1970 Model was conceptually simple at expense of computer overhead 13 Database Systems, 10 th Edition
The Relational Model (cont'd. ) Relational data management system (RDBMS) Performs same functions provided by hierarchical model Hides complexity from the user Relational diagram Representation of entities, attributes, and relationships Relational table stores collection of related entities 14 Database Systems, 10 th Edition
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The Relational Model (cont'd. ) SQL-based relational database application involves three parts: End-user interface Allows end user to interact with the data Set 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 17 Database Systems, 10 th Edition
The Entity Relationship Model Widely accepted standard for data modeling Introduced by Chen in 1976 Graphical representation of entities and their relationships in a database structure Entity relationship diagram (ERD) Uses graphic representations to model database components Entity is mapped to a relational table 18 Database Systems, 10 th Edition
The Entity Relationship Model (cont'd. ) Entity instance (or occurrence) is row in table Entity set is collection of like entities Connectivity labels types of relationships Relationships are expressed using Chen notation Relationships are represented by a diamond Relationship name is written inside the diamond Crow's Foot notation used as design standard in this book 19 Database Systems, 10 th Edition
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Emerging Data Models: Big Data and No. SQL Big Data Find new and better ways to manage large amounts of Web-generated data and derive business insight from it Simultaneously provides high performance and scalability at a reasonable cost Relational approach does not always match the needs of organizations with Big Data challenges 21 Database Systems, 10 th Edition
Emerging Data Models: Big Data and No. SQL (cont'd. ) No. SQL databases Not based on the relational model, hence the name No. SQL Supports distributed database architectures Provides high scalability, high availability, and fault tolerance Supports very large amounts of sparse data Geared toward performance rather than transaction consistency 22 Database Systems, 10 th Edition
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Degrees of Data Abstraction Database designer starts with abstracted view, then adds details ANSI Standards Planning and Requirements Committee (SPARC) Defined a framework for data modeling based on degrees of data abstraction (1970 s): External Conceptual Internal 24 Database Systems, 10 th Edition
The External Model End users' view of the data environment ER diagrams represent external views External schema: specific representation of an external view Entities Relationships Processes Constraints 25 Database Systems, 10 th Edition
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The External Model (cont'd. ) Easy to identify specific data required to support each business unit's operations Facilitates designer's job by providing feedback about the model's adequacy Ensures security constraints in database design Simplifies application program development 27 Database Systems, 10 th Edition
The Conceptual Model Represents global view of the entire database All external views integrated into single global view: conceptual schema ER model most widely used ERD graphically represents the conceptual schema 28 Database Systems, 10 th Edition
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The Conceptual Model (cont'd. ) Provides a relatively easily understood macro level view of data environment Independent of both software and hardware Does not depend on the DBMS software used to implement the model Does not depend on the hardware used in the implementation of the model Changes in hardware or software do not affect database design at the conceptual level 30 Database Systems, 10 th Edition
The Internal Model Representation of the database as "seen" by the DBMS Maps the conceptual model to the DBMS Internal schema depicts a specific representation of an internal model Depends on specific database software Change in DBMS software requires internal model be changed Logical independence: change internal model without affecting conceptual model 31 Database Systems, 10 th Edition
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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 33 Database Systems, 10 th Edition
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Summary A data model is an abstraction of a complex realworld data environment Basic data modeling components: Entities Attributes Relationships Constraints Business rules identify and define basic modeling components 35 Database Systems, 10 th Edition
Summary (cont'd. ) Hierarchical model Set of one-to-many (1: M) relationships between a parent and its children segments Network data model Uses sets to represent 1: M relationships between record types Relational model Current database implementation standard ER model is a tool for data modeling Complements relational model 36 Database Systems, 10 th Edition
Summary (cont'd. ) Object-oriented data model: object is basic modeling structure Relational model adopted object-oriented extensions: extended relational data model (ERDM) OO data models depicted using UML Data-modeling requirements are a function of different data views and abstraction levels Three abstraction levels: external, conceptual, and internal 37 Database Systems, 10 th Edition
Database Systems Design Implementation and Management 10th Edition Chapter 2
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