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Lecture Business system development - Lecture 14: Structuring system logical requirements

Lecture 14 - Structuring system logical requirements. In this lecture, we will: Define four types of business rules, compare the capabilities of class diagrams vs. E-R diagrams, relate data modeling to process and logic modeling. | Business System Development CSC581 Lecture 14 Structuring System Logical Requirements 2 Summary of the previous lecture In previous lecture, we : Defined key data modeling terms. Drew entity-relationship (E-R) and class diagrams to represent common business situations. Explained the role of conceptual data modeling in IS analysis and design. Distinguished between unary, binary, and ternary relationships. Outlines We today’s lecture we will: Define four types of business rules. Talk about the class diagrams Compare the capabilities of class diagrams vs. E-R diagrams. Relate data modeling to process and logic modeling Business Rules Specifications that preserve the integrity of the logical data model Four types Entity integrity: unique, non-null identifiers Referential integrity constraints: rules governing relationships Domains: valid values for attributes Triggering operations: other business rules regarding attribute values Domains The set of all data types and ranges of values . | Business System Development CSC581 Lecture 14 Structuring System Logical Requirements 2 Summary of the previous lecture In previous lecture, we : Defined key data modeling terms. Drew entity-relationship (E-R) and class diagrams to represent common business situations. Explained the role of conceptual data modeling in IS analysis and design. Distinguished between unary, binary, and ternary relationships. Outlines We today’s lecture we will: Define four types of business rules. Talk about the class diagrams Compare the capabilities of class diagrams vs. E-R diagrams. Relate data modeling to process and logic modeling Business Rules Specifications that preserve the integrity of the logical data model Four types Entity integrity: unique, non-null identifiers Referential integrity constraints: rules governing relationships Domains: valid values for attributes Triggering operations: other business rules regarding attribute values Domains The set of all data types and ranges of values that an attribute can assume Several advantages Verify that the values for an attribute are valid Ensure that various data manipulation operations are logical Help conserve effort in describing attribute characteristics 8 Triggering Operations An assertion or rule that governs the validity of data manipulation operations such as insert, update and delete Components: User rule: statement of the business rule to be enforced by the trigger Event: data manipulation operation that initiates the operation Entity Name: name of entity being accessed or modified Condition: condition that causes the operation to be triggered Action: action taken when the operation is triggered 9 Packaged Data Models Generic data models that can be applied and modified for an organization Two categories Universal Industry-specific Benefits Reduced implementation time and cost High-quality modeling Packaged data models provide generic models that can be customized for a particular organization’s business rules Object