Using The Invoice Table Structure Shown In Table P63

Using The Invoice Table Structure Shown In Table P63 Do The Followin

Using the INVOICE table structure shown in Table P6.3, do the following: a. Write the relational schema, draw its dependency diagram, and identify all dependencies, including all partial and transitive dependencies. You can assume that the table does not contain repeating groups and that an invoice number references more than one product. (Hint: This table uses a composite primary key.) b. Remove all partial dependencies, write the relational schema, and draw the new dependency diagrams. Identify the normal forms for each table structure you created. c. Remove all transitive dependencies, write the relational schema, and draw the new dependency diagrams. Also identify the normal forms for each table structure you created. d. Draw the Crow’s Foot ERD.

Paper For Above instruction

Introduction

Database normalization is a fundamental process in designing relational databases that ensures data integrity, reduces redundancy, and enhances query performance. The task involves analyzing an existing table structure to identify its dependencies and normal forms, and subsequently refining the schema to comply with higher normalization standards. Additionally, creating an Entity-Relationship Diagram (ERD) provides a visual representation of the data structure and relationships, facilitating better understanding and communication among database stakeholders.

Analysis of the Invoice Table Structure

The given table, referred to as Table P6.3, presumably contains fields such as invoice number, product details, and possibly customer data. The table's primary key is a composite, likely comprising invoice number and product ID, especially if an invoice references multiple products, which is a typical scenario in sales databases. The initial step involves writing the relational schema based on this structure. For illustration, consider a hypothetical schema:

Invoice(ProductID, InvoiceNumber, Quantity, Price, CustomerID, InvoiceDate)

This schema indicates that each record captures a specific product within an invoice, including quantities, prices, and customer information.

Dependency Diagram and Dependency Identification

In the initial schema, the potential dependencies could include:

• Composite primary key: (InvoiceNumber, ProductID)
• Functional dependencies such as:
• InvoiceNumber → CustomerID, InvoiceDate
• ProductID → Price
• (InvoiceNumber, ProductID) → Quantity, Price

Partial dependencies exist when a non-key attribute depends on part of a composite key; for example, CustomerID and InvoiceDate depend solely on InvoiceNumber, not on the entire composite. Transitive dependencies occur when non-key attributes depend on other non-key attributes, such as Price depending on ProductID, which in turn depends on InvoiceNumber.

Removing Partial Dependencies

To achieve 2NF, partial dependencies need to be eliminated by decomposing the original schema into smaller relations where each non-key attribute depends entirely on the primary key. The tables might be:

Invoices(InvoiceNumber, CustomerID, InvoiceDate)
InvoiceDetails(InvoiceNumber, ProductID, Quantity, Price)
Products(ProductID, Price)

Here, the 'Invoices' table captures invoice-specific data, while 'InvoiceDetails' records the products associated with each invoice. 'Products' maintains product-specific details.

Removing Transitive Dependencies

Further normalization to 3NF involves removing transitive dependencies. For instance, if 'Price' in 'InvoiceDetails' depends on 'ProductID', which is only dependent on 'Products', this dependency should be handled by separating the product data entirely. The schema might become:

Invoices(InvoiceNumber, CustomerID, InvoiceDate)
InvoiceDetails(InvoiceNumber, ProductID, Quantity)
Products(ProductID, Price)

Each table now contains only directly related attributes, following 3NF principles. The 'Price' is stored in 'Products', removing transitive dependencies from 'InvoiceDetails'.

Drawing the Crow’s Foot ERD

The ERD visually exhibits the relationships: 'Invoices' links to 'InvoiceDetails' through 'InvoiceNumber'; 'InvoiceDetails' links to 'Products' via 'ProductID'. The Crow’s Foot notation indicates 'one-to-many' relationships from invoices to invoice details and from products to invoice details.

Normal Forms and Conclusion

The initial table likely violated 1NF due to potential repeating groups, while the decompositions achieve 2NF and 3NF by eliminating partial and transitive dependencies, respectively. The final normalized schema ensures data integrity and consistency within the database structure. Visualizing relationships through the Crow’s Foot ERD enhances clarity for database design and implementation, supporting efficient querying and data management.

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