Presentation on theme: "System Analysis - Data Modeling"— Presentation transcript:
1 System Analysis - Data Modeling 4/16/2017Chapter 2System Analysis- Data Modeling
2 Learning Objectives Define key data modeling terms. 4/16/2017Learning ObjectivesDefine key data modeling terms.Draw entity-relationship (E-R) to represent common business situations.Explain the role of conceptual data modeling in IS analysis and design.Distinguish between unary, binary, and ternary relationships.
4 Conceptual Data Modeling 4/16/2017Conceptual Data ModelingA detailed model that captures the overall structure of data in an organizationIndependent of any database management system (DBMS) or other implementation considerations
5 Process of Conceptual Data Modeling 4/16/2017Process of Conceptual Data ModelingDevelop a data model for the current systemDevelop a new conceptual data model that includes all requirements of the new systemIn the design stage, the conceptual data model is translated into a physical designProject repository links all design and data modeling steps performed during SDLC
6 Deliverables and Outcome 4/16/2017Deliverables and OutcomePrimary deliverable is an entity-relationship (E-R) diagram or class diagramAs many as 4 E-R or class diagrams are produced and analyzedE-R diagram that covers data needed in the project’s applicationE-R diagram for the application being replacedE-R diagram for the whole database from which the new application’s data are extractedE-R diagram for the whole database from which data for the application system being replaced is drawn
7 Deliverables and Outcome (cont.) 4/16/2017Deliverables and Outcome (cont.)Second deliverable is a set of entries about data objects to be stored in repository or project dictionary.Repository links data, process, and logic models of an information system.Data elements included in the DFD must appear in the data model and vice versa.Each data store in a process model must relate to business objects represented in the data model.
9 Requirements Determination Questions for Data Modeling 4/16/2017Requirements Determination Questions for Data ModelingWhat are subjects/objects of the business?Data entities and descriptionsWhat unique characteristics distinguish between subjects/objects of the same type?Primary keysWhat characteristics describe each subject/object?Attributes and secondary keysHow do you use the data?Security controls and user access privileges
10 Requirements Determination Questions for Data Modeling (cont.) 4/16/2017Requirements Determination Questions for Data Modeling (cont.)Over what period of time are you interested in the data?Cardinality and time dimensionsAre all instances of each object the same?Supertypes, subtypes, and aggregationsWhat events occur that imply associations between objects?Relationships and cardinalitiesAre there special circumstances that affect the way events are handled?Integrity rules, cardinalities, time dimensions
11 Introduction to Entity-Relationship (E-R) Modeling 4/16/2017Introduction to Entity-Relationship (E-R) ModelingEntity-Relationship (E-R) DiagramA detailed, logical representation of the entities, associations and data elements for an organization or businessNotation uses three main constructsData entitiesRelationshipsAttributes
12 Association between the instances of one or more entity types 4/16/2017Association between the instances of one or more entity typesPerson, place, object, event or concept about which data is to be maintainedEntity type: collection of entities with common characteristicsEntity instance: single entitynamed property or characteristic of an entity
13 ENTITY Types of Entity Example Person STAFF, STUDENT, LECTURER Place 4/16/2017ENTITYTypes of EntityExamplePersonSTAFF, STUDENT, LECTURERPlaceSTATE, TOWNObjectEventConceptBUILDING, TOOL, PRODUCTCOURSE, ACCOUNTREGISTRATION, APPLICATION
14 Identifier Attributes 4/16/2017Identifier AttributesCandidate keyAttribute (or combination of attributes) that uniquely identifies each instance of an entity typeIdentifierA candidate key that has been selected as the unique identifying characteristic for an entity type
15 Identifier Attributes (cont.) 4/16/2017Identifier Attributes (cont.)Selection rules for an identifierChoose a candidate key that will not change its value.Choose a candidate key that will never be null.Avoid using intelligent keys.Consider substituting single value surrogate keys for large composite keys.
16 Multivalued Attributes 4/16/2017Multivalued AttributesAn attribute that may take on more than one value for each entity instanceRepresented on E-R Diagram in two ways:double-lined ellipseweak entity
17 Entity and Attribute Example 4/16/2017Entity and Attribute ExampleSimple attributesIdentifier attribute… each employee has a unique ID.Multivalued attribute… an employee may have more than one skill.
18 Degree of Relationship 4/16/2017Degree of RelationshipDegree: number of entity types that participate in a relationshipThree casesUnary: between two instances of one entity typeBinary: between the instances of two entity typesTernary: among the instances of three entity types
20 4/16/2017CardinalityThe number of instances of entity B that can or must be associated with each instance of entity AMinimum CardinalityThe minimum number of instances of entity B that may be associated with each instance of entity AMaximum CardinalityThe maximum number of instances of entity B that may be associated with each instance of entity AMandatory vs. Optional CardinalitiesSpecifies whether an instance must exist or can be absent in the relationship
24 4/16/2017Associative EntitiesAn entity type that associates the instances of one or more entity types and contains attributes that are peculiar to the relationship between those entity instancesAn associative entity is:An entityA relationshipThis is the preferred way of illustrating a relationship with attributes
25 A relationship with an attribute 4/16/2017A relationship with an attribute…as an associative entity
26 …as an associative entity 4/16/2017Ternary relationship…as an associative entity
27 4/16/2017A relationship that itself is related to other entities via another relationship must be represented as an associative entity.
28 Summary In this chapter you learned how to: 4/16/2017SummaryIn this chapter you learned how to:Define key data modeling terms.Draw entity-relationship (E-R) to represent common business situations.Explain the role of conceptual data modeling in IS analysis and design.Distinguish between unary, binary, and ternary relationships.