or repository would include the data flow’s composition, which then tells us what data are flowing in or out of the data store. For example, the Amounts Used data flow coming from Process 2.0 indicates how much to decrease an attribute STOCK_ON_HAND due to use of the INVENTORY ITEM to fulfill a customer sale. Thus, the Amounts Used data flow implies that Process 2.0 will first read the relevant INVENTORY ITEM record, then update its STOCK_ON_HAND attribute, and finally store the updated value in the record. Each data flow would be analyzed similarly (space does not permit us to show the analysis for each data flow). After having considered all data flows in and out of data stores related to data entities, plus all decision logic related to inventory control, we derive the full E-R diagram, with attributes, shown in Figure 7-11. In Visio, the ITEM SALE, RECIPE, and INVOICE ITEM entities participate in what are called Thus, Visio treats identifying relationships. them as associative entities, not just the RECIPE entity. Visio automatically includes the primary keys of the identifying entities as primary keys in the identified (associative) entities. Also note that in Visio, because it cannot represent many-to-many relationships, there are two mandatory relationships on either side of RECIPE. FIGURE 7-11 Final E-R Diagram for Hoosier Burger’s Inventory Control System PVF WebStore: Conceptual Data Modeling Conceptual data modeling for an Internet-based electronic commerce application is no different from the process followed when analyzing the data needs for other types of applications. In the last chapter, you read how Jim Woo analyzed the flow of information within the WebStore and developed a data-flow diagram. In this section, we examine the process he followed when developing the WebStore’s conceptual data model. Conceptual Data Modeling for Pine Valley
or repository would include the data flow’s composition, which then tells us what data are flowing in or out of the data store. For example, the Amounts Used data flow coming from Process 2.0 indicates how much to decrease an attribute STOCK_ON_HAND due to use of the INVENTORY ITEM to fulfill a customer sale. Thus, the Amounts Used data flow implies that Process 2.0 will first read the relevant INVENTORY ITEM record, then update its STOCK_ON_HAND attribute, and finally store the updated value in the record. Each data flow would be analyzed similarly (space does not permit us to show the analysis for each data flow). After having considered all data flows in and out of data stores related to data entities, plus all decision logic related to inventory control, we derive the full E-R diagram, with attributes, shown in Figure 7-11. In Visio, the ITEM SALE, RECIPE, and INVOICE ITEM entities participate in what are called identifying relationships. Thus, Visio treats them as associative entities, not just the RECIPE entity. Visio automatically includes the primary keys of the identifying entities as primary keys in the identified (associative) entities. Also note that in Visio, because it cannot represent many-to-many relationships, there are two mandatory relationships on either side of RECIPE. FIGURE 7-11 Final E-R Diagram for Hoosier Burger’s Inventory Control System PVF WebStore: Conceptual Data Modeling Conceptual data modeling for an Internet-based electronic commerce application is no different from the process followed when analyzing the data needs for other types of applications. In the last chapter, you read how Jim Woo analyzed the flow of information within the WebStore and developed a data-flow diagram. In this section, we examine the process he followed when developing the WebStore’s conceptual data model. Conceptual Data Modeling for Pine Valley
104758_1_assignment.docx