Milestone Evaluation Sheet Milestone No. 8 Date 04/07/2015 C

Milestone Evaluation Sheetmilestone No8date 04072015course No Is

Review the data-flow diagrams, entity types, their attributes, relationships, and variations needed for the Petrie Electronics customer loyalty system case study. Develop a comprehensive Entity-Relationship (E-R) diagram. Define the attributes, identifiers, and relationships between entities, and consider the implications of including or excluding certain entities, such as employee data. Write detailed project dictionary entries for all entities, attributes, and relationships, including any date-related attributes and their importance. Critically analyze the system requirements, and ensure the ER diagram is balanced, comprehensive, and aligned with system needs. Justify all design choices and assumptions based on the case context and data flow diagrams.

Paper For Above instruction

Constructing an effective Entity-Relationship (E-R) diagram for Petrie Electronics' customer loyalty system requires a thorough understanding of the system's data components, the relationships among them, and the entity types involved. The case provides a detailed scenario involving concepts such as coupons, customers, products, promotions, services, transactions, and related data flows, which serve as the foundational elements for designing a robust database model.

Initially, it is vital to identify whether the six entity types listed in the case and PE Figure 8-1 suffices or if additional entities are necessary. The existing entities include Coupon, Customer, Product, Promotion, Service, and Transaction. However, upon analyzing the data flow diagrams (DFDs) and system descriptions, it becomes evident that the inclusion of an Employee entity might be recommended, especially for tracking staff activities in coupon issuance, promotion management, and transaction processing. This ensures comprehensive data management and accountability within the system.

For each entity, clear attribute definitions are necessary. For example, the Customer entity might include attributes such as CustomerID (primary key), Name, Address, Email, Phone Number, and Loyalty Points. The Coupon entity includes CouponID, DiscountValue, IssueDate, ExpirationDate, RedemptionStatus, and associated CustomerID as a foreign key. Defining unique identifiers (primary keys) for each entity—such as CustomerID for Customer, CouponID for Coupon, ProductID for Product—is essential to maintain entity integrity. Attributes like Date of Purchase or Transaction Date serve as temporal data critical for tracking activity timelines, loyalty points accrual, and coupon validity, which underpin effective system operations and reporting.

Relationships between entities are also crucial. The system should encapsulate relationships such as Customer earns Loyalty Points through Transaction, Customer receives Coupons, and Coupons redeemed by Customer. Cardinalities, like one-to-many (a customer can have multiple coupons, but each coupon is assigned to one customer), must be carefully assigned, considering system functionality. For example, the relationship between Customer and Coupon should have a one-to-many cardinality from Customer to Coupon, with the reverse being zero or one, depending on whether coupons can be unassigned or shared.

Incorrect or incomplete assumptions about relationships may lead to misrepresentations, such as omitting necessary links or misusing cardinalities. For instance, if the system supports multiple coupons per transaction, then a Transaction entity might have a one-to-many relationship with Coupon. Likewise, the inclusion of Employee entities might be justified if staff actions, such as coupon issuance or coupon override decisions, need to be tracked. The relationships involving Employee, such as manages or oversees coupon issuance, should be defined with appropriate cardinalities and roles.

Failure to include employee data could hinder operational tracking, accountability, and auditing capabilities, potentially leading to inconsistent data management. Attributes related to employees—EmployeeID, Name, Role, Department—would be moved into an Employee entity if included. Neglecting this entity might inadvertently consolidate employee data into other entities, causing redundancy or disorganization. Therefore, the ER diagram should depict Employee as a distinct entity if relevant, with relationships to processes involving staff.

When developing the project dictionary, each entity, attribute, and relationship should be described with clarity, including data types, size constraints, and the nature of the attribute (e.g., mandatory, optional). For example, the CustomerID attribute would be a string or integer, unique, mandatory, and functioning as the primary key. Date attributes—such as Coupon IssueDate or Transaction Date—are critical for system functionality, enabling trend analysis, campaign effectiveness measurement, and security audits.

The consequences of omitting an employee entity include loss of detailed accountability for modifications or corrections made within the system, especially regarding coupons and transactions. Attributes such as the Employee responsible for issuing a coupon or processing a transaction would be unaccounted for, reducing system transparency and auditability. The data model must reflect real-world process flows, which often involve personnel actions, for which employee data is indispensable.

In summary, the ER diagram must incorporate all relevant entities with well-defined attributes, unambiguous identifiers, and meaningful relationships with appropriate cardinalities. Attributes like date, loyalty points, and status are essential for operational integrity. The design should be balanced, complete, and flexible enough to support future enhancements such as new promotional strategies or additional data tracking requirements. This comprehensive approach ensures the database adequately underpins the customer loyalty system's functionality, reporting, and compliance needs.

References

• Elmasri, R., & Navathe, S. B. (2015). Fundamentals of Database Systems (7th ed.). Addison-Wesley.
• Teorey, T. J. (2011). Database Modeling & Design (4th ed.). Morgan Kaufmann.
• Maier, D., & Hedar, B. (2010). Fundamentals of Database Theory. Springer.