Perform Normalization On A Crude Table

In This Task You Will Perform Normalization On A Crude Table So That

In this task, you will perform normalization on a crude table so that it could be stored as a relational database. The staff at 'Franklin Consulting' have to routinely visit their clients in other cities. Franklin have a fleet of cars available for staff travels. During their trips, the staff sometimes need to fill up the car fuel. Upon returning from the trip, the staff claim that expenses back by providing the fueling receipt and some other essential information. The accountant records all of that information in a spreadsheet. Below are the spreadsheet column headers and a sample of data from each column.

Paper For Above instruction

Introduction

Normalization is a fundamental process in designing relational databases, aiming to reduce redundancy and improve data integrity. The scenario involving Franklin Consulting provides a practical example of how unnormalized data, typically stored in spreadsheets, can be transformed into a well-structured relational database through normalization procedures. This paper discusses the steps involved in normalization, focusing on the First Normal Form (1NF), Second Normal Form (2NF), and Third Normal Form (3NF), using the context of Franklin Consulting's travel and expense data.

Understanding the Initial Unnormalized Data

The initial dataset likely contains multiple repeating groups and dependencies, making it inefficient for database implementation. For instance, a single row might include information about the staff member, their trip details, the vehicle used, fuel receipts, and expenses, all intertwined. This structure leads to redundancy—for example, the same staff member or vehicle information might be repeated across multiple rows—and inconsistency risks if data is updated in only some instances. To address these issues, normalization systematically decomposes the data into multiple related tables, each representing a single subject or entity.

First Normal Form (1NF)

Achieving 1NF involves ensuring that all data entries are atomic—that is, indivisible—meaning each field contains only a single value. For Franklin Consulting, this requires examining the spreadsheet and eliminating fields that contain multiple values, such as multiple fuel receipts or multiple trip destinations within a single record. Each record must be unique, with no repeating groups or arrays in any column. For example, instead of listing multiple fuel types or receipts in one cell, each should be stored as separate records linked through foreign keys. The primary goal is to organize data into a table where each intersection of row and column contains a single, atomic value.

Second Normal Form (2NF)

To attain 2NF, the database must first be in 1NF, and all non-key attributes must depend entirely on the primary key. This often involves identifying composite keys—keys composed of multiple columns—and removing partial dependencies. Applying 2NF to Franklin's data entails creating separate tables for entities such as Staff, Vehicles, Trips, and Expenses. For instance, the Staff table would contain staff IDs and their details; the Vehicle table would store vehicle information; and the Trip table would link staff and vehicles with trip-specific data. Fuel receipts and expenses should be stored in their respective tables, linked via foreign keys to the trip or staff records. This process minimizes redundancy, such as repeating staff details in every trip record.

Third Normal Form (3NF)

Achieving 3NF requires the database to be in 2NF, with all transitive dependencies removed—that is, non-key attributes should depend only on the primary key, not on other non-key attributes. For Franklin Consulting, this involves further decomposing data so that related entities are stored in separate tables, and all non-key data are directly dependent on their primary keys. For example, if the vehicle's manufacturer details are stored alongside vehicle information, this data should be moved to a separate Manufacturer table, linked via a foreign key. This prevents anomalies and ensures data consistency.

Practical Implementation

Implementing normalization in Franklin Consulting's case involves several steps:

1. Identifying entities such as Staff, Vehicles, Trips, Fueling, and Expenses.

2. Creating separate tables for each entity with appropriate primary keys.

3. Establishing relationships between these tables using foreign keys—e.g., linking a Trip record to Staff and Vehicle tables.

4. Ensuring all tables comply with 1NF by atomic data.

5. Eliminating partial dependencies for 2NF.

6. Removing transitive dependencies to achieve 3NF.

Benefits of Normalization

Normalization enhances the efficiency and integrity of the database by reducing data redundancy and preventing update anomalies. For Franklin Consulting, a normalized database allows for easier maintenance, accurate data retrieval, and reporting. For example, updates to staff details need to be made only once in the Staff table, rather than repeatedly across multiple records. Moreover, normalization sets the foundation for advanced database functions such as indexing and query optimization.

Conclusion

Transforming Franklin Consulting's unnormalized spreadsheet data into a normalized relational database involves systematic steps that ensure data is organized efficiently and accurately. Starting from ensuring atomicity, progressing through eliminating partial and transitive dependencies, normalization minimizes redundancy and maintains data integrity. Implementing the appropriate normalization forms enhances operational efficiency, data consistency, and scalability of the database for future needs. This process exemplifies best practices in database design, vital for robust data management in modern organizations.

References

1. Communications of the ACM, 13(6), 377-387.
2. Fundamentals of Database Systems (7th ed.). Pearson.
3. Database Management Systems (3rd ed.). McGraw-Hill.
4. Conceptual Database Design: An Entity-Relationship Approach. Benjamin/Cummings.
5. Database System Concepts (6th ed.). McGraw-Hill.
6. An Introduction to Database Systems. Addison-Wesley.
7. Database Systems: A Practical Approach to Design, Implementation, and Management (6th ed.). Pearson.
8. Database Concepts (7th ed.). Pearson.
9. A First Course in Database Systems. Pearson.
10. An Introduction to Database Systems (8th ed.). Pearson.