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Data Models

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data models

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  • Data Models

  • ObjectivesWhy data models are importantAbout the basic data-modeling building blocksWhat business rules are and how they influence database designHow the major data models evolvedHow data models can be classified by level of abstraction

  • The Importance of Data ModelsData models Relatively simple representations, usually graphical, of complex real-world data structuresFacilitate interaction among the designer, the applications programmer, and the end user

  • The Importance of Data Models (continued)End-users have different views and needs for dataData model organizes data for various users

  • Data Model Basic Building BlocksEntity - anything about which data are to be collected and storedAttribute - a characteristic of an entityRelationship - describes an association among entitiesOne-to-many (1:M) relationship Many-to-many (M:N or M:M) relationshipOne-to-one (1:1) relationshipConstraint - a restriction placed on the data

  • Business RulesBrief, precise, and unambiguous descriptions of a policies, procedures, or principles within a specific organizationApply to any organization that stores and uses data to generate informationDescription of operations that help to create and enforce actions within that organizations environment

  • Business Rules (continued)Must be rendered in writing Must be kept up to dateSometimes are external to the organizationMust be easy to understand and widely disseminatedDescribe characteristics of the data as viewed by the company

  • Discovering Business RulesSources of Business Rules:Company managersPolicy makersDepartment managersWritten documentationProceduresStandardsOperations manualsDirect interviews with end users

  • Translating Business Rules into Data Model ComponentsStandardize companys view of dataConstitute a communications tool between users and designersAllow designer to understand the nature, role, and scope of dataAllow designer to understand business processesAllow designer to develop appropriate relationship participation rules and constraintsPromote creation of an accurate data model

  • Discovering Business Rules (continued)Generally, nouns translate into entitiesVerbs translate into relationships among entitiesRelationships are bi-directional

  • The Evolution of Data Models (continued)HierarchicalNetworkRelationalEntity relationshipObject oriented (OO)

  • The Hierarchical ModelDeveloped in the 1960s to manage large amounts of data for complex manufacturing projectsBasic logical structure is represented by an upside-down tree

  • The Hierarchical Model (continued)

  • The Hierarchical Model (continued)The hierarchical structure contains levels, or segmentsDepicts a set of one-to-many (1:M) relationships between a parent and its children segments Each parent can have many childreneach child has only one parent

  • The Hierarchical Model (continued)AdvantagesMany of the hierarchical data models features formed the foundation for current data modelsIts database application advantages are replicated, albeit in a different form, in current database environmentsGenerated a large installed (mainframe) base, created a pool of programmers who developed numerous tried-and-true business applications

  • The Hierarchical Model (continued)DisadvantagesComplex to implementDifficult to manageLacks structural independenceImplementation limitationsLack of standards

  • The Network ModelCreated to Represent complex data relationships more effectively Improve database performanceImpose a database standardConference on Data Systems Languages (CODASYL) Database Task Group (DBTG)

  • The Network Model (continued)SchemaConceptual organization of entire database as viewed by the database administratorSubschemaDefines database portion seen by the application programs that actually produce the desired information from data contained within the database Data Management Language (DML) Defines the environment in which data can be managed

  • The Network Model (continued)Schema Data Definition Language (DDL)Enables database administrator to define schema componentsSubschema DDLAllows application programs to define database components that will be usedDML Works with the data in the database

  • The Network Model (continued)Resembles hierarchical modelCollection of records in 1:M relationshipsSetRelationshipComposed of at least two record typesOwner Equivalent to the hierarchical models parent MemberEquivalent to the hierarchical models child

  • The Network Model (continued)

  • The Network Model (continued)DisadvantagesToo cumbersomeThe lack of ad hoc query capability put heavy pressure on programmersAny structural change in the database could produce havoc in all application programs that drew data from the databaseMany database old-timers can recall the interminable information delays

  • The Relational ModelDeveloped by Codd (IBM) in 1970Considered ingenious but impractical in 1970Conceptually simple Computers lacked power to implement the relational modelToday, microcomputers can run sophisticated relational database software

  • The Relational Model (continued)Relational Database Management System (RDBMS)Performs same basic functions provided by hierarchical and network DBMS systems, in addition to a host of other functionsMost important advantage of the RDBMS is its ability to hide the complexities of the relational model from the user

  • The Relational Model (continued)Table (relations) Matrix consisting of a series of row/column intersectionsRelated to each other through sharing a common entity characteristicRelational diagramRepresentation of relational databases entities, attributes within those entities, and relationships between those entities

  • The Relational Model (continued)Relational TableStores a collection of related entitiesResembles a fileRelational table is purely logical structureHow data are physically stored in the database is of no concern to the user or the designerThis property became the source of a real database revolution

  • The Relational Model (continued)

  • The Relational Model (continued)

  • The Relational Model (continued)Rise to dominance due in part to its powerful and flexible query languageStructured Query Language (SQL) allows the user to specify what must be done without specifying how it must be doneSQL-based relational database application involves:User interfaceA set of tables stored in the databaseSQL engine

  • The Entity Relationship ModelWidely accepted and adapted graphical tool for data modeling Introduced by Chen in 1976Graphical representation of entities and their relationships in a database structure

  • The Entity Relationship Model (continued)Entity relationship diagram (ERD)Uses graphic representations to model database componentsEntity is mapped to a relational tableEntity instance (or occurrence) is row in table Entity set is collection of like entitiesConnectivity labels types of relationshipsDiamond connected to related entities through a relationship line

  • The Entity Relationship Model (continued)

  • The Entity Relationship Model (continued)

  • The Object Oriented ModelModeled both data and their relationships in a single structure known as an objectObject-oriented data model (OODM) is the basis for the object-oriented database management system (OODBMS)OODM is said to be a semantic data model

  • The Object Oriented Model (continued)Object described by its factual content Like relational models entityIncludes information about relationships between facts within object, and relationships with other objectsUnlike relational models entitySubsequent OODM development allowed an object to also contain all operationsObject becomes basic building block for autonomous structures

  • The Object Oriented Model (continued)Object is an abstraction of a real-world entityAttributes describe the properties of an objectObjects that share similar characteristics are grouped in classesClasses are organized in a class hierarchyInheritance is the ability of an object within the class hierarchy to inherit the attributes and methods of classes above it

  • The Object Oriented Model (continued)

  • Other ModelsExtended Relational Data Model (ERDM)Semantic data model developed in response to increasing complexity of applicationsDBMS based on the ERDM often described as an object/relational database management system (O/RDBMS)Primarily geared to business applications

  • Database Models and the InternetInternet drastically changed role and scope of database marketOODM and ERDM-O/RDM have taken a backseat to development of databases that interface with InternetDominance of Web has resulted in growing need to manage unstructured information

  • Data Models: A SummaryEach new data model capitalized on the shortcomings of previous modelsCommon characteristics: Conceptual simplicity without compromising the semantic completeness of the databaseRepresent the real world as closely as possibleRepresentation of real-world transformations (behavior) must comply with consistency and integrity characteristics of any data model

  • Data Models: A Summary (continued)

  • Degrees of Data AbstractionWay of classifying data modelsMany processes begin at high level of abstraction and proceed to an ever-increasing level of detailDesigning a usable database follows the same basic process

  • Degrees of Data Abstraction (continued)American National Standards Institute (ANSI) Standards Planning and Requirements Committee (SPARC)Defined a framework for data modeling based on degrees of data abstraction(1970s): ExternalConceptualInternal

  • Degrees of Data Abstraction (continued)

  • The External ModelEnd users view of the data environmentRequires that the modeler subdivide set of requirements and constraints into functional modules that can be examined within the framework of their external models

  • The External Model (continued)Advantages:Easy to identify specific data required to support each business units operationsFacilitates designers job by providing feedback about the models adequacyCreation of external models helps to ensure security constraints in the database designSimplifies application program development

  • The External Model (continued)

  • The Conceptual ModelRepresents global view of the entire databaseRepresentation of data as viewed by the entire organizationBasis for identification and high-level description of main data objects, avoiding detailsMost widely used conceptual model is the entity relationship (ER) model

  • The Conceptual Model (continued)

  • The Conceptual Model (continued)Provides a relatively easily understood macro level view of data environmentIndependent 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 modelChanges in either hardware or DBMS software have no effect on the database design at the conceptual level

  • The Internal ModelRepresentation of the database as seen by the DBMSMaps the conceptual model to the DBMSInternal schema depicts a specific representation of an internal model

  • The Internal Model (continued)

  • The Physical ModelOperates at lowest level of abstraction, describing the way data are saved on storage media such as disks or tapesSoftware and hardware dependentRequires that database designers have a detailed knowledge of the hardware and software used to implement database design

  • The Physical Model (continued)

  • SummaryA data model is a (relatively) simple abstraction of a complex real-world data environmentBasic data modeling components are:EntitiesAttributesRelationshipsConstraints

  • Summary (continued)Hierarchical modelDepicts a set of one-to-many (1:M) relationships between a parent and its children segmentsNetwork data modelUses sets to represent 1:M relationships between record typesRelational modelCurrent database implementation standardER model is a popular graphical tool for data modeling that complements the relational model

  • Summary (continued)Object is basic modeling structure of object oriented data modelThe relational model has adopted many object-oriented extensions to become the extended relational data model (ERDM)Data modeling requirements are a function of different data views (global vs. local) and level of data abstraction


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