SYSTEMS ANALYSIS AND DESIGN [2242-INSY-3305]Spring 2024 | Instructor: Atieno A. AmadiAssignment-3 Logical Data ModelInstructions:Draw a logical data model (ERD) for the Picnics R US case [Refer to ‘Assignment#1’ and‘Assiignment#2’ on Canvas under ‘Assignments’]Guidelines:A data model describes the data that flow through the business processes in anorganization. It represents the logical [rather than physical] organization of data]. Lateron in the system development process, the data model is changed to reflect exactly howthe data will be stored in databases and files.Hints:Whereas a process model (DFD) represents how the business system will operate, adata model (ERD) represents how the data that flow through the processes areorganized and presented. A data model is a formal way of representing the data that areused and created by a business system. Data stores of the DFD generally correspond toentities of the ERD: Identify the entities Add appropriate attributes for each entity Draw the relationships that connect associated entities Check the process models for data stores, external entities, and data flows Check the major inputs and outputs from the use cases Identify attributes of the entity that are relevant to the system under development Check the process model repository entries for details on data flows anddata stores Check the data requirements of the requirements definition Select each entity’s candidate identifier Start with an entity and identify all entities with which it shares relationships Determine the cardinality and modality of the relationshipsPageof 2ZOOMSYSTEMS ANALYSIS AND DESIGN [2242-INSY-3305]Spring 2024 | Instructor: Atieno A. AmadiAssignment-3 Logical Data ModelInstructions:Draw a logical data model (ERD) for the Picnics R US case [Refer to ‘Assignment#1’ and‘Assiignment#2’ on Canvas under ‘Assignments’]Guidelines:A data model describes the data that flow through the business processes in anorganization. It represents the logical [rather than physical] organization of data]. Lateron in the system development process, the data model is changed to reflect exactly howthe data will be stored in databases and files.Hints:Whereas a process model (DFD) represents how the business system will operate, adata model (ERD) represents how the data that flow through the processes areorganized and presented. A data model is a formal way of representing the data that areused and created by a business system. Data stores of the DFD generally correspond toentities of the ERD: Identify the entities Add appropriate attributes for each entity Draw the relationships that connect associated entities Check the process models for data stores, external entities, and data flows Check the major inputs and outputs from the use cases Identify attributes of the entity that are relevant to the system under development Check the process model repository entries for details on data flows anddata stores Check the data requirements of the requirements definition Select each entity’s candidate identifier Start with an entity and identify all entities with which it shares relationships Determine the cardinality and modality of the relationships More Information on Logical Data ModelsHow Does A Logical Data Model Work?Logical data models serve as an abstraction layer, defining the relationships between differentdata elements, entities, and attributes. Unlike a physical data model, which is specific to aparticular database system, a logical data model focuses on the business concepts and rulesthat govern the data.Entities, Relationships, and AttributesEntities are the fundamental building blocks of a logical data model, representing objects orconcepts—customers, products, or orders, for example. Relationships define how these entitiesare connected or associated with each other, while attributes describe the characteristics orproperties of the entities.Benefits of Logical Data ModelingLogical data modeling activities help organizations unearth areas for business processimprovement as an emergent benefit that arises from the design of well-informed applications.Because they require establishing the structure of data elements and the relationships betweenthem, logical data models and their design and implementation activities often reveal myriadpreviously unknown improvements and optimizations, helping organizations streamline existingdata management processes and make better-informed business decisions:Improved Data ComprehensionA key advantage that logical data models provide is a clear and comprehensive view ondata. By mapping out the relationships between different data elements in easy-to-understand/minimal notation, a range of stakeholders—for example, business analystsand database administrators—can more easily grasp the intricacies of the organization’sdata and its relevance to the business processes.Better CommunicationLogical data models serve as the common language for bridging the communication gapamong various stakeholders involved in the data management process. From softwareengineers and developers to data scientists and analysts and business users andcustomers, a standardized logical data model facilitates effective communication amongall data stakeholders, ensuring that all parties with visibility into the model are on thesame page when discussing data requirements and structures.
RUBRIC
Rubric for Assignment-3 Logical Data ModelInstructions:Draw a logical data model (ERD) for the Picnics R US case [Refer to ‘Assignment#1’ and‘Assiignment#2’ on Canvas under ‘Assignments’]Rubric: 30% – Identify the entities 15% – Add appropriate attributes for each entity 15% – Assign identifies for each entity 15% – Draw the relationships that connect associated entities 15% – Determine the cardinality between all related entities Identify any Intersection/Associative Entities 10% – Indicate the modality of the relationship between related entities
