Review The Dfds You Developed For The Petries Electron

Again Review The Dfds You Developed For The Petries Electronics C

Again, review the DFDs you developed for the Petrie’s Electronics case (or those given to you by your instructor). Use these DFDs to identify the attributes of each of the six entities listed in this case plus any additional entities identified in your answer to Question 1. Write an unambiguous definition for each attribute. Then, redraw PE Figure 7-1 by placing the six (and additional) entities in this case on the diagram along with their associated attributes.

Using your answer to Question 2, designate which attribute or attributes form the identifier for each entity type. Explain why you chose each identifier.

Using your answer to Question 3, draw the relationships between entity types needed by the system. Remember, a relationship is needed only if the system wants data about associated entity instances. Give a meaningful name to each relationship. Specify cardinalities for each relationship and explain how you decided on each minimum and maximum cardinality at each end of each relationship. State any assumptions you made if the Petrie’s Electronics cases you have read so far and the answers to questions in these cases do not provide the evidence to justify the cardinalities you choose. Redraw your final E-R diagram in Microsoft Visio.

Paper For Above instruction

Again Review The Dfds You Developed For The Petries Electronics C

In the context of designing a database system for Petrie’s Electronics, a systematic review of Data Flow Diagrams (DFDs) is essential. DFDs, as visual representations of information movement within a system, serve as foundational artifacts to identify critical entities, processes, data stores, and data flows. They provide the necessary insights to determine the attributes of various entities that the system records and manages. This paper will elucidate how to analyze existing DFDs to extract entity attributes, formulate unambiguous attribute definitions, identify primary identifiers, and subsequently develop a comprehensive Entity-Relationship (E-R) diagram that accurately models the system’s data architecture.

Identification of Entities and Attributes from DFDs

The first step involves examining the DFDs associated with Petrie’s Electronics—either previously developed or provided by an instructor. These diagrams illustrate the flow of data related to customers, orders, products, suppliers, employees, and possibly other relevant entities. Each entity has unique attributes that describe its characteristics. To accurately model these, one must analyze data inputs, outputs, and storage points illustrated in the DFDs.

For example, the customer entity likely includes attributes such as Customer ID, Name, Address, Phone Number, and Email. Each attribute must be precisely defined. Customer ID, for instance, is a unique code assigned to each customer for identification purposes. The same process applies to other entities: for orders (Order ID, Date, Total Amount), products (Product Code, Name, Description, Price), suppliers (Supplier ID, Name, Contact Information), and employees (Employee ID, Name, Position, Department).

Additional entities may emerge from extended analysis, such as Sales Transactions, Shipments, or Payment Records, each with its own set of attributes. Writing unambiguous definitions involves clarifying each attribute's purpose, data type, possible values, and constraints. For example, 'Order Date' is a date attribute representing when the order was placed, and it must follow the standard date format with validation rules.

Redrawing the ER Diagram with Entities and Attributes

Once attributes are defined, the next step is to redraw the diagram akin to PE Figure 7-1, positioning the identified entities and their attributes. Each entity is represented as a rectangle labeled with the entity name, and attributes are ovals connected to their respective entities. Some attributes are underlined to denote primary keys. Ensuring clarity and correctness in this diagram helps visualize the data structure and prepares for defining relationships.

Determining Entity Identifiers

Designating the primary key for each entity involves selecting attribute(s) that uniquely identify each instance. For example, Customer ID is suitable as a primary key for the Customer entity because it is unique to each customer. The choice of identifiers must follow criteria such as uniqueness, minimality, stability, and simplicity. For the Orders entity, Order ID is an appropriate primary key since each order receives a unique identifier.

Choosing appropriate identifiers facilitates data integrity and simplifies referencing in relationships. The rationale for each choice is based on the attribute’s ability to uniquely distinguish entity instances, consistency, and its use in establishing foreign keys.

Modeling Entity Relationships

With entities and their identifiers established, the next phase involves drawing the relationships between entities that the system requires. Relationships are only modeled when the system needs to store and manage data about associated entity instances. For instance, an Order is placed by a Customer; hence, a relationship exists between Customer and Order entities, named 'Places.'

Similarly, a Product may belong to a Supplier, establishing a 'Supplied By' relationship. The relationship's cardinality—minimum and maximum—must be justified: for example, a customer may place many orders (one-to-many), but an order is placed by exactly one customer (one-to-one). These cardinalities are based on business rules, system requirements, or assumptions if not explicitly stated.

The minimum cardinality (participation constraint) indicates whether an instance must participate in the relationship (e.g., every order must be associated with a customer), while the maximum specifies the allowed number of related instances (e.g., an order can contain many products, but each product can be in many orders—a many-to-many relationship that may require an associative entity).

Finally, the complete final E-R diagram is redrawn using a diagramming tool like Microsoft Visio, ensuring clarity, correctness, and adherence to the identified attributes, keys, relationships, and cardinalities.

Conclusion

Accurate extraction of entity attributes from DFDs, precise definition of primary keys, and careful modeling of relationships are crucial steps in designing an effective data architecture for Petrie’s Electronics. These steps ensure that the system encapsulates all necessary information about entities and their associations, supporting robust database development and efficient data management.

References

• Clemons, J. M., & Hemphill, T. A. (2009). Fundamentals of Database Systems (4th ed.). Cengage Learning.