You Developed And Revised Your ERD In Week Two Bringing You ✓ Solved

You Developed And Revised Your Erd In Week Two Bringing You One Step

Explain the purpose of the normalization process including a description for each of the five normal forms (1NF, 2NF, 3NF, 4NF, and 5NF) and providing examples for each. Cite the sources for all examples. You will then translate the ERD model you created and revised in Week Two into 3NF.

Within your paper, explain how each table in your ERD meets 1NF, 2NF, and 3NF. If the tables do not meet the forms, you need to resolve any issues and normalize the database to meet 1NF, 2NF, and 3NF. If issues were encountered and had to be resolved, describe the rules that were violated and how you resolved them.

Sample Paper For Above instruction

The process of normalization in relational database design is fundamental in organizing data efficiently, minimizing redundancy, and maintaining data integrity. Normalization involves structuring a database in accordance with a series of normal forms, each with specific rules to ensure data is stored logically and free from anomalies. This process allows database designers to create reliable and scalable systems that can handle complex queries with ease and consistency.

Purpose of Normalization

The primary purpose of normalization is to eliminate data redundancy and inconsistency, ensuring that each piece of data is stored in only one place. Normalization also simplifies data maintenance and improves database performance by reducing data anomalies during insertion, update, or deletion operations. Moreover, it facilitates logical data organization, which is crucial for efficient query processing and data retrieval.

Overview of the Five Normal Forms

First Normal Form (1NF)

1NF requires that all table columns contain atomic, indivisible values, and that each record is unique. In other words, the table should not contain repeating groups or arrays. For example, a customer table with multiple phone numbers stored in one field violates 1NF; instead, each phone number should be stored as a separate record or in a related table.

Second Normal Form (2NF)

2NF builds on 1NF by requiring that all non-key attributes are fully functionally dependent on the primary key. This involves removing partial dependencies, which occur when a non-key attribute depends only on part of a composite primary key. For instance, in an order details table where the primary key is composite (OrderID, ProductID), if the product name depends only on ProductID, this violates 2NF. In such cases, separating product information into a separate table resolves the dependency.

Third Normal Form (3NF)

3NF requires that the table is in 2NF and that no transitive dependencies exist, meaning non-key attributes should not depend on other non-key attributes. For example, if a table contains CustomerID, CustomerName, and CustomerCity, and CustomerCity depends on CustomerID, this is acceptable. However, if CustomerCity depends on CustomerName, this violates 3NF; the city information should move to a separate customer details table.

Fourth Normal Form (4NF)

4NF addresses multivalued dependencies, ensuring that no table contains two or more independent and multivalued attributes that are related to the primary key. For instance, if a student table includes multiple courses and multiple hobbies listed in multi-valued fields, splitting these into separate tables avoids 4NF violations.

Fifth Normal Form (5NF)

5NF, also known as projection-join normal form, ensures that data can be reconstructed from smaller, less detailed tables without loss of information, addressing join dependencies. This form is used in complex databases where data redundancies are minimized. For example, in a sales database with products, sales regions, and sales reps, decomposing the data into tables that can be reconstructed accurately embodies 5NF principles.

Application of Normalization to ERD

Transforming my ERD from Week Two into 3NF involved analyzing each table to ensure compliance with the normalization principles. For example, my original Customer table contained CustomerID, CustomerName, CustomerCity, and CustomerType, which initially seemed compliant with 1NF. However, I identified a transitive dependency where CustomerCity depended on CustomerType, which is determined by CustomerID. To resolve this, I created a separate CustomerType table with TypeID and TypeDescription, assigning customers to types via foreign keys, thus eliminating the transitive dependency and achieving 3NF.

Similarly, my OrderDetails table had OrderID, ProductID, Quantity, and ProductName. Since ProductName depended solely on ProductID, to meet 2NF, I created a separate Products table with ProductID and ProductName, linking it with OrderDetails via foreign keys. This normalization prevented partial dependency issues and ensured that updates to product information only needed to be made in one table, reducing anomalies.

During this process, I recognized that my initial design had some multivalued attributes, such as a customer's multiple contact numbers stored in a single field. Resolving this involved creating a separate ContactNumbers table with CustomerID and ContactNumber, ensuring compliance with 4NF. This step minimized redundancy and maintained data consistency across the database.

In conclusion, normalization is essential in designing a robust relational database. It systematically reduces redundancy and dependency issues, facilitating efficient data management. My ERD's transformation into 3NF improved data integrity, query performance, and scalability, ensuring the database aligns with best practices in relational database design.

References

• Codd, E. F. (1970). A relational model of data for large shared data banks. Communications of the ACM, 13(6), 377-387.