Identify And Discuss The Serious Data Redundancy Problems

Identify and discuss the serious data redundancy problems exhibited by the file structure...

Identify and discuss the serious data redundancy problems exhibited by the file structure shown in Figure P1.5. Looking at the EMP_NAME and EMP_PHONE contents in Figure P1.5, what change(s) would you recommend? Identify the various data sources in the file examined in Problem 5. Given your answer to Problem 7, what new files should you create to help eliminate the data redundancies found in the file shown in Figure P1.5? Identify and discuss the serious data redundancy problems exhibited by the file structure shown in Figure P1.9. Describe the relationships (identify the business rules) depicted in the Crow’s Foot ERD shown in Figure P2.13. Create a Crow’s Foot ERD to include the specified business rules for the ProdCo Company: each sales representative writes many invoices; each invoice is written by one sales representative; each sales representative is assigned to one department; each department has many sales representatives; each customer can generate many invoices; each invoice is generated by one customer. Write the business rules reflected in the ERD shown in Figure P2.15.

Sample Paper For Above instruction

Data redundancy presents a significant challenge in database design, often leading to data inconsistency, storage inefficiency, and increased maintenance overhead. Examining the file structure in Figure P1.5 reveals several redundant data issues, particularly concerning employee information such as EMP_NAME and EMP_PHONE. These redundancies typically occur when employee details are duplicated across multiple records, making updates cumbersome and error-prone. For example, multiple invoice records might contain the same employee's name and phone number, leading to potential inconsistencies if contact details change.

To address these issues, normalization techniques should be adopted. Specifically, separate employee information into a dedicated Employee table that includes unique Employee IDs, names, and phone numbers. The invoice records would then reference employees through their Employee IDs, ensuring that any update to employee data propagates uniformly across all related records. This approach reduces redundancy and maintains data integrity.

The various data sources in the analyzed file include the employee details, invoice records, customer information, and departmental data. Each of these can be transformed into separate, related tables—Employees, Invoices, Customers, and Departments. For example, the initial flat file may amalgamate employee and invoice data, causing duplication. By segregating data sources into normalized tables, redundancies are minimized.

In response to these data sources, new files should be created: an Employee file containing unique employee records, a Customer file, and a Department file. The Invoice file should then include foreign keys linking to these entities. This design eliminates redundant employee and customer data across multiple invoices, improving data consistency, query efficiency, and ease of maintenance.

Furthermore, examining the file structure in Figure P1.9 indicates similar redundancy issues, perhaps in different data domains. Transitioning to a relational model, with properly defined tables and relationships, would resolve these duplicate data problems. For instance, establishing one-to-many relationships between departments and employees or between customers and invoices ensures each entity's data is stored only once, with references connecting related records.

The relationships depicted in the Crow’s Foot ERD in Figure P2.13 can be interpreted as representing key business rules—such as departments having many sales representatives and each invoice being linked to a specific customer and sales representative. These relationships validate the logical model of the business functions.

Building a new ERD for the ProdCo Company involves implementing these rules: sales representatives write many invoices (one-to-many), each invoice has one sales representative (many-to-one), relationships exist between sales reps and departments, and between customers and invoices. The diagram should depict these relationships clearly with Crow’s Foot notation, emphasizing the cardinality constraints.

The business rules embedded in the ERD in Figure P2.15 correspond to these relationships and constraints, confirming that the data structure accurately models the business processes. These rules establish the foundations for designing a normalized database schema that effectively supports the application's data integrity and operational requirements.

References

• Elmasri, R., & Navathe, S. B. (2016). Database Systems (6th ed.). Pearson.