St. Ambrose CSCI 300 - DATA MODELING AND ANALYSIS

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PowerPoint PresentationChapter Seven Data Modeling and AnalysisChapter MapSystem ModelsData ModelingSample Entity Relationship Diagram (ERD)Simple Data Flow DiagramA Modern Data ArchitectureData Modeling Concepts: EntityData Modeling Concepts: AttributesData Modeling Concepts: DomainsData Modeling Concepts: IdentificationData Modeling Concepts: Identification Keys & Subsetting CriteriaData Modeling Concepts: RelationshipsData Modeling Concepts: CardinalityData Modeling Concepts: DegreeSlide 17Slide 18Data Modeling Concepts: Foreign KeysSlide 20Slide 21Slide 22Resolving Nonspecific Relationships (continued)Slide 24Data Modeling Concepts: GeneralizationGeneralization HierarchySlide 27Irwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionC H A P T E R7DATA MODELING AND ANALYSISIrwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionChapter Seven Data Modeling and Analysis•Define systems modeling and differentiate between logical and physical system models.•Define data modeling and explain its benefits.•Recognize and understand the basic concepts and constructs of a data model.•Read and interpret an entity relationship data model.•Explain when data models are constructed during a project and where the models are stored.•Discover entities and relationships.•Construct an entity-relationship context diagram.•Discover or invent keys for entities and construct a key-based diagram.•Construct a fully attributed entity relationship diagram and describe all data structures and attributes to the repository or encyclopedia.•Normalize a logical data model to remove impurities that can make a database unstable, inflexible, and nonscalable. •Describe a useful tool for mapping data requirements to business operating locations.Irwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionChapter MapIrwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionSystem ModelsA model is a representation of reality. Logical models show what a system is or does. They are implementation independent; that is, they depict the system independent of any technical implementation. Physical models shows what a system is or does and how the system is physically and technically implemented.Irwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionData ModelingData modeling is a technique for organizing and documenting a system’s data. Data modeling is sometimes called database modeling because a data model is eventually implemented as a database. It is sometimes called information modeling. The actual model is called an entity relationship diagram because it depicts data in terms of the entities and relationships described by the data.Irwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionSample Entity Relationship Diagram (ERD)Irwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionSimple Data Flow DiagramIrwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionA legacyfile-basedinformationsystem(builtin-house)FileFileInformationSystem(builtin-house)InformationSystem(builtin-house)OperationalDatabaseFileFileInformation System(built in-house)A legacyfile-basedinformationsystem(purchased)FileFileFileInformationSystem(purchased)DataWarehouseEnd-UserToolsEnd-UserApplicationsUsers andProgrammersUsers andProgrammersUsers andProgrammersUsers andProgrammersUsersEnd-UserWork GroupWork-GroupDatabasePersonalDBOperationalDatabaseA Modern Data ArchitectureIrwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionPersons: agency, contractor, customer, department, division, employee, instructor, student, supplier. Places: sales region, building, room, branch office, campus. Objects: book, machine, part, product, raw material, software license, software package, tool, vehicle model, vehicle. Events: application, award, cancellation, class, flight, invoice, order, registration, renewal, requisition, reservation, sale, trip. Concepts: account, block of time, bond, course, fund, qualification, stock. Name of EntityData Modeling Concepts: EntityAn entity is a class of persons, places, objects, events, or concepts about which we need to capture and store data.Irwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionSTUDENTNa me.Last Name.First Name.Middle InitialAddress.Street Address.City.State or Province.Country.Postal CodePhone Number.Area Code.Exchange Number.Number Within ExchangeDate of BirthGenderRaceMajorGrade Poin t AverageData Modeling Concepts: AttributesAn attribute is a descriptive property or characteristic of an entity. Synonyms include element, property, and field. A compound attribute (structured data type) is one that actually consists of other attributesIrwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionData Modeling Concepts: Domains•Data type –defines what type of data can be stored•Character•Date/Time•Integer•Currency•Domain –values a attribute can legitimately take on.•Default value – the value that will be recorded if not specified by the user•Not Null•NullIrwin/McGraw-HillCopyright © 2000 The McGraw-Hill Companies. All Rights reservedWhitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS 5th EditionData Modeling Concepts: Identification•Key –unique value for each that identifies anentity instance. –Group of attributes •concatenated key. –Candidate key •a “candidate to become the primary key” –Primary key •a candidate key that will most commonly be


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St. Ambrose CSCI 300 - DATA MODELING AND ANALYSIS

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