Unformatted text preview:

PowerPoint PresentationObjectivesChapter MapSystem ModelsData ModelingSlide 6A 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 16Slide 17Data Modeling Concepts: Foreign KeysSlide 19Slide 20Slide 21Resolving Nonspecific Relationships (continued)Slide 23Data Modeling Concepts: GeneralizationGeneralization HierarchySlide 26Strategic Data ModelingData Modeling During Systems AnalysisSlide 29Data Modeling StepsData Modeling DiscoverySlide 32EntitiesEntity Discovery for SoundStageThe Context Data ModelThe Key-based Data ModelThe Key-based Data Model With GeneralizationThe Fully-Attributed Data ModelData Analysis & NormalizationNormalization: 1NF, 2NF, 3NFFirst Normal Form ExampleNormalization: 2NFSecond Normal Form ExampleSlide 44Slide 45Third Normal Form ExampleSlide 47SoundStage 3NF Data ModelData-to-Location-CRUD MatrixSlide 50C H A P T E R8DATA MODELING AND ANALYSISObjectives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Read and interpret an entity relationship data model.Explain when data models are constructed during a project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Normalize a logical data model to make a database more stable, flexible, and scalable. Describe a useful tool for mapping data requirements to business operating locations.Chapter MapSystem 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.Data 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.A 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 Architecture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.STUDENTNa 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 (composite) attribute (structured data type) is one that actually consists of other attributesData 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NullData Modeling Concepts: IdentificationKey –unique value for each that identifies anentity instance. –Group of attributes concatenated (composite) key. –Candidate key a “candidate to become the primary key” –Primary key a candidate key that will most commonly be used to uniquely identify a single entity instance–Alternate keycandidate key that is not selected to become the primary key Subsetting criteria–divide all entity instances into useful subsets.Data Modeling Concepts: Identification Keys & Subsetting CriteriaSTUDENTStudent Number (Primary Key)Social Security Number (Alternate Key)Name.Last Name.First Name.Middle InitialAddress.Street Address.City.State or Province.Country.Postal CodePhone Number.Area Code.Exchange Number.Number Within ExchangeDate of BirthGender (Subsetting Criteria 1)Race (Subsetting Criteria 2)Major (Subsetting Criteria 3)Grade Po int AverageData Modeling Concepts: RelationshipsRelationship –A natural business association between one or more entities. –May represent an event that links the entities –A logical affinity that exists between the entities.bidirectionalData Modeling Concepts: CardinalityCardinality –defines the minimum and maximum number of occurrences of one entity that may be related to a single occurrence of the other entity. –all relationships are bidirectional, cardinality must be defined in both directions for every relationship. Degree of a relationship is the number of entities that participate in the relationship.Data Modeling Concepts: DegreeA recursive relationship is a relationship that exists between different instances of the same entityData Modeling Concepts: DegreeRelationships may exist between more than two entities and are called N-ary relationships. The example ERD depicts a ternary (WHY?) relationship.Data Modeling Concepts: DegreeAn


View Full Document

St. Ambrose CSCI 300 - Data Modeling

Download Data Modeling
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view Data Modeling and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view Data Modeling 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?