FILE SYSTEMS & DATABASE 1.5: Data Models DB2 ITS232 Introduction To Database Oracle MySQL MS Access FILE SYSTEMS & DATABASE 1.5: Data Models Chapter 1

Data Models The Importance of Data Models Relatively simple representations, usually graphical, of complex real-world data structures 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 Models 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 Constraint a restriction placed on the data/user-defined structures that let you restrict the behaviors of columns/attributes

Data Models Data Model Basic Building Blocks Based on previous IBM DB2 lab, determine: Entity PERSON, VEHICLE, BUILDING, PLANT, ANIMAL, etc Attribute person_name, animal_family, scientific_name, etc Relationship 1:1, 1:M, M:N Constraint NOT NULL, CHECK, PRIMARY KEY, FOREIGN KEY, TRIGGER

Data Models Business Rules Brief, precise, and unambiguous 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 that help to create and enforce actions within that organization’s environment

Data Models Business Rules Must be rendered in writing/available in written form Must be kept up to date Sometimes are external to the organization Must be easy to understand and widely distributed Describe characteristics of the data as viewed by the company: corresponds to a table (ERD) Entities associations between entities Relationships characteristics of entities Attributes describe the relationship classification (min & max) Connectivity limitations on the type of data accepted Constraints

Data Models Discovering Business Rules Sources of Business Rules: Company managers Policy makers Department managers Written documentation Procedures Standards Operations manuals Direct interviews with end users

Data Models Discovering Business Rules Business rules example:

Data Models Translating Business Rules into Data Model Components Standardize company’s view of data Act as a communications tool between users and designers Allow designer: to understand the nature, role, and scope of data to understand business processes to develop appropriate relationship participation rules and constraints Promote creation of an accurate data model

Data Models Discovering Business Rules Generally Nouns translate into entities Verbs translate into relationships among entities Relationships are bi-directional Fact finding techniques: The formal process of using techniques such as interview and questionnaire to collect facts about system, requirements and preferences. To captures the essential facts necessary to build the required database What facts are collected? Captured facts about the current and/or future system.

Data Models Fact Finding Techniques Examining documents (document review) Interviewing Observation the organization in operations Research Questionnaire 5 commonly used fact finding techniques

Data Models The Evolution of Data Models Hierarchical Database Model Represented by a group of records that relates to each others by a pointer Network Database Model Based on set theory, a set consists a collection of records Relational Database Model Based on the mathematical concept of relational Object-Oriented Model Based on object oriented concepts

Data Models The Evolution of Data Models Developed in the 1960s to manage large amounts of data for complex manufacturing projects Basic logical structure is represented by an upside-down “tree” or by a group of records that relates to each others by a pointer The uppermost record is a Root The lower record in a hierarchy is a Child Depicts a set of one-to-many (1:M) relationships between a parent and its children segments Each parent can have many children each child has only one parent Hierachical Database Model

Data Models The Evolution of Data Models Hierachical Database Model

Data Models The Evolution of Data Models Hierachical Database Model Abu Johor 3000 Samad Kedah 2500 A001 A002 A003 Nut Washer Hammer Bolt Root A004 Zaitun Melaka 4500

Data Models The Evolution of Data Models Hierachical Database Model Root Segment Source: http://worldacademyonline.com/article/25/359/data_models__relational__hierarchical_and_network_.html

Data Models The Evolution of Data Models Advantages Many of the hierarchical data model’s features formed the foundation for current data models Its database application advantages are replicated, albeit in a different form, in current database environments Generated a large installed (mainframe) base, created a pool of programmers who developed numerous tried-and-true business applications Hierachical Database Model

Data Models The Evolution of Data Models Develop in 1970 in Conference on Data Systems Languages (CODASYL), by Database Task Group (DBTG) Created to Represent complex data relationships more effectively Improve database performance Impose a database standard Resembles hierarchical model Collection of records in 1:M relationships Network Database Model

Data Models The Evolution of Data Models Set Relationship Composed of at least two record types Owner Equivalent to the hierarchical model’s parent Member Equivalent to the hierarchical model’s child A parent can have many child records A child can have more than one parent record Network Database Model

Data Models The Evolution of Data Models Network Database Model

Data Models The Evolution of Data Models Network Database Model Abu Samad Zaitun Johor Kedah Melaka 3000 2500 4500 A001 A002 A003 Nut Washer Hammer Bolt A004 CUSTOMER PRODUCT INVOICE

Data Models The Evolution of Data Models Network Database Model Source: http://worldacademyonline.com/article/25/359/data_models__relational__hierarchical_and_network_.html

Data Models The Evolution of Data Models Disadvantages Too cumbersome/difficult to handle The lack of ad hoc query capability put heavy pressure on programmers Any structural change in the database could produce havoc in all application programs that drew data from the database Many database old-timers can recall the interminable information delays Network Database Model

Data Models The Evolution of Data Models Developed by Codd (IBM) in 1970 considered ingenious but impractical in 1970 Conceptually simple, based on mathematical concept of relational Computers lacked power to implement the relational model Today, microcomputers can run sophisticated relational database software Relational Database Management System (RDBMS) Performs same basic functions provided by hierarchical and network DBMS systems, in addition to a host of other functions Most important advantage of the RDBMS is its ability to hide the complexities of the relational model from the user Relational Model

Data Models The Evolution of Data Models Relational Model Matrix consisting of a series of row/column intersections Related to each other through sharing a common entity characteristic Table (relations) Representation of relational database’s entities, attributes within those entities, and relationships between those entities Relational diagram Stores a collection of related entities Resembles a file Relational Table How data are physically stored in the database is of no concern to the user or the designer This property became the source of a real database revolution Relational table is purely logical structure

Data Models The Evolution of Data Models Example of table structure/relational table Relational Model

Data Models The Evolution of Data Models Example of table with data/relational table Relational Model

Data Models The Evolution of Data Models Example of table relationship/relational diagram Relational Model

Data Models The Evolution of Data Models Example of form Relational Model

Data Models The Evolution of Data Models Rise to dominance due in part to its powerful and flexible query language Structured Query Language (SQL) allows the user to specify what must be done without specifying how it must be done SQL-based relational database application involves: User interface A set of tables stored in the database SQL engine Relational Model

Data Models The Evolution of Data Models Entity Relationship (E-R) Model Introduced by Chen in 1976 Widely accepted and adapted graphical tool for data modeling Graphical representation of entities and their relationships in dB structure Entity Relationship Diagram (ERD) Uses graphic representations to model database components Entity is mapped to a relational table Relational Model

Data Models The Evolution of Data Models Example of ERD Relational Model Chen Crow’s Foot

Data Models The Evolution of Data Models Modeled both data and their relationships in a single structure known as an object OO data model (OODM) is the basis for the OO database management system (OODBMS) Object Oriented Model

Data Models The Evolution of Data Models Object described by its factual content equivalent to entity in Relational Model Includes information about relationships between facts within object, and relationships with other objects but still unlike relational model’s entity Subsequent OODM development allowed an object to also contain all operations: changing its data values, finding specific data values, printing data values Object becomes basic building block for autonomous structures Object Oriented Model

Data Models The Evolution of Data Models Object is an abstraction of a real-world entity E.g. PERSON, VEHICLE Attributes describe the properties of an object E.g. Name, IC Number, Address Objects that share similar characteristics are grouped in classes Shared structured (attributes) and behavior (methods) Classes are organized in a class hierarchy Inheritance is the ability of an object within the class hierarchy to inherit the attributes and methods of classes above it Object Oriented Model

Data Models The Evolution of Data Models A comparison of the OO model and the ER model Object Oriented Model

Data Models A Summary Each new data model capitalized on the shortcomings of previous models Common characteristics: Conceptual simplicity without compromising the semantic completeness of the database Represent the real world as closely as possible Representation of real-world transformations (behavior) must comply with consistency and integrity characteristics of any data model

Data Models A Summary: The development of data model Semantic data - data is organized in such a way that it can be interpreted meaningfully without human intervention

Data Models Degrees of Data Abstraction Way of classifying data models Many processes begin at high level of abstraction and proceed to an ever-increasing level of detail Designing a usable database follows the same basic process The major purpose of a database system is to provide users with an abstract view of the system. The system hides certain details of how data is stored and created and maintained Complexity should be hidden from database users.

Data Models Degrees of Data Abstraction American National Standards Institute (ANSI) Standards Planning and Requirements Committee (SPARC) Defined a framework for data modeling based on degrees of data abstraction (1970s): The famous “Three Level ANSI-SPARC Architecture” External Conceptual Internal

Data Models Degrees of Data Abstraction Data abstraction levels

Data Models Three Level ANSI-SPARC Architecture View 1 View 2 View n Conceptual Schema Internal Schema Database User n User 2 User 1 … -user’s view External Model 1. External level ERD Conceptual Model -designer’s view -h/w independent -s/w independent 2. Conceptual level -DBMS’s view -h/w independent -s/w dependent Internal Model 3. Internal level -h/w dependent -s/w dependent Physical Model Physical data organization

Three Level ANSI-SPARC Architecture External Model End users’ view of the data environment Requires that the modeler subdivide set of requirements and constraints into functional modules that can be examined within the framework of their external models Advantages: 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 Creation of external models helps to ensure security constraints in the database design Simplifies application program development

Three Level ANSI-SPARC Architecture External Model Example of External Model for Tiny College

Three Level ANSI-SPARC Architecture Conceptual Model Global view of the entire database  concept of the dB Describe what data is stored in the dB and relations among the data Data as viewed by the entire organization  logical structure Basis for identification and high-level description of main data objects, avoiding details Most widely used conceptual model is the entity relationship (ER) model Provides a relatively easily understood macro level view of data environment Software and Hardware Independent 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 either hardware or DBMS software have no effect on the database design at the conceptual level

Three Level ANSI-SPARC Architecture Conceptual Model Example of Conceptual Model for Tiny college

Three Level ANSI-SPARC Architecture Internal Model Representation of the database as “seen” by the DBMS Describes how the data is stored in the dB Maps the conceptual model to the DBMS Internal schema depicts a specific representation of an internal model Physical representation of the dB on the computer Software Dependent and Hardware Independent Depend on the DBMS software used to implement the model Does not depend on the hardware used in the implementation of the model

Three Level ANSI-SPARC Architecture Internal Model An Internal Model for Tiny College

Three Level ANSI-SPARC Architecture Physical Model The Physical Model Operates at lowest level of abstraction, describing the way data are saved on storage media such as disks or tapes how the data is stored in the database Software and Hardware Dependent Requires that database designers have a detailed knowledge of the hardware and software used to implement database design

Three Level ANSI-SPARC Architecture Physical Model The Physical Model

Summary of Data Models The Evolution of Data Models A data model is a (relatively) simple abstraction of a complex real-world data environment Basic data modeling components are: _____________________ Data modeling requirements are a function of different data views (global vs. local) and level of data abstraction

Summary of Data Models The Evolution of Data Models Hierarchical Database Model _________________________________________________ Network Database Model ________________________________________________ Relational Database Model _____________________________________________ Object-Oriented Model

Summary of Data Models Three Level ANSI-SPARC Architecture View 1 View 2 View n Conceptual Schema Internal Schema Database User n User 2 User 1 … -user’s view 1. External level -designer’s view -h/w independent -s/w independent ERD 2. Conceptual level -DBMS’s view -h/w independent -s/w dependent Internal Model 3. Internal level -h/w dependent -s/w dependent Physical Model Physical data organization