Technical Data Management And Applications Assignment 41 Des
Technical Data Management And Applicationsassignment 41 Describe The
Describe the purpose of normalizing data. (5 points)
Discuss the alternative ways that normalization can be used to support database design (5 points)
Describe the types of update anomalies that may occur on a relation that has redundant data (5 points)
Describe the concept of functional dependency (5 points)
What are the main characteristics of functional dependencies that are used when normalizing a relation? (5 points)
Describe and show the process of normalizing the table below to at least 3NF relations. Show the keys in your relations. (25 points)
| staffNo | dentistName | patNo | patName | Appointment date | time | surgeryNo |
|---|---|---|---|---|---|---|
| S1011 | Tony Smith | P100 | Gillian White | 12/09/08 | 10.00 | S15 |
| S1011 | Tony Smith | P105 | Jill Bell | 12/09/08 | 12.00 | S15 |
| S1024 | Helen Pearson | P108 | Ian MacKay | 12/09/08 | 10.00 | S10 |
| S1024 | Helen Pearson | P108 | Ian MacKay | 14/09/08 | 14.00 | S10 |
| S1032 | Robin Plevin | P105 | Jill Bell | 14/09/08 | 16.00 | S15 |
| S1032 | Robin Plevin | P110 | John Walker | 15/09/08 | 18.00 | S13 |
Paper For Above instruction
Normalization of data is a fundamental process in database design aimed at reducing redundancy and improving data integrity. The primary purpose of normalizing data is to organize the fields and tables of a database to minimize duplicate data and ensure logical data dependencies. By doing so, normalization facilitates efficient database maintenance, supports accurate data retrieval, and prevents anomalies that can compromise data quality.
Normalization can be employed in various ways to support robust database design beyond merely eliminating redundancy. It serves as a systematic methodology to decompose complex tables into simpler, well-structured relations that adhere to specific normal forms—first (1NF), second (2NF), and third (3NF). Furthermore, normalization helps in establishing clear functional dependencies, which define the relationships among the data attributes and guide the creation of foreign keys to maintain referential integrity. Normalization also aids in detecting anomalies and designing updates that do not lead to inconsistent data states, thereby ensuring data consistency across the database.
Update anomalies are common issues arising from redundant data within relations. These anomalies include insertion anomalies, where adding new data becomes problematic because some required data is missing or incomplete; deletion anomalies, where deleting a record inadvertently results in the loss of important information; and update anomalies, where modifications in redundant data lead to inconsistencies because the same data is stored in multiple places. For example, in a denormalized relation, updating a patient's address in one record but not others can cause discrepancies. These anomalies highlight the need to normalize database relations to ensure consistency and efficient data management.
The concept of functional dependency is central to the process of normalization. It describes a relationship where the value of one set of attributes (the determinant) uniquely determines the value of another set of attributes. In other words, in a relation, if the value of attribute A determines the value of attribute B, then B is functionally dependent on A, denoted as A → B. Functional dependencies help in understanding the data's inherent rules and constraints, enabling the design of relations that adhere to these rules while avoiding redundancy and anomalies.
The main characteristics of functional dependencies used in normalization include their consistency, closure, and minimal cover. In practice, the process involves identifying candidate keys—minimal sets of attributes that functionally determine all other attributes in the relation. Functional dependencies help in identifying whether a relation violates the normal forms, especially when dependencies are partial (dependent on part of a candidate key) or transitively dependent (dependent through another attribute). Recognizing these dependencies is crucial in decomposition processes to achieve higher normal forms such as 2NF and 3NF, where relations are free from partial and transitive dependencies, respectively.
The normalization process of the provided table aims to decompose it into relations conforming to at least 3NF by identifying primary keys, functional dependencies, and removing redundancies while maintaining data integrity. Initially, the composite key includes staffNo, patNo, and appointment date, which determine other attributes but lead to redundancy in attributes like dentistName and surgeryNo. Steps involve isolating entities such as staff, patients, appointments, and surgeries, each represented in separate relations with appropriate primary keys.
The first step involves creating a Staff relation based on staffNo and dentistName, where staffNo is the primary key. The Patient relation includes patNo and patName, with patNo as its primary key. The Appointment relation contains staffNo, patNo, appointment date, and time, with a composite key of staffNo, patNo, and appointment date, representing each unique appointment. Lastly, a Surgery relation includes surgeryNo and potentially other attributes, with surgeryNo as its primary key. These decompositions eliminate redundancy, ensure each relation represents a single entity, and are linked via foreign keys, aligning with the principles of 3NF.