Assignment Submission: Write Your Solutions In A Word File
Assignment Submissionwrite Your Solutions In A Word File Type Your Na
Assignment Submissionwrite Your Solutions In A Word File Type Your Na
Assignment Submissionwrite Your Solutions In A Word File Type Your Na
Assignment Submission Write your solutions in a Word file, type your name and course number in that file, name it. This the question down below: QUESTION . To keep track of books it sells, a B Club book store uses the table structure shown below. Assuming that the sample data are representative, draw a dependency diagram in Visio that shows all functional dependencies including both partial and transitive dependencies. ( Hint: Look at the sample values to determine the nature of the relationships.) Attribute NameSample ValueSample ValueSample ValueBOOK_CODE BOOK_TITLE History of RomeNew LegendIntro to Databases GENRE_CODE H23M12F01 GENRE_DESCRIP HistoryMysteryComputers AUTHOR_ID 3399, AUTHOR_NAME Robert Knut, John SmithRobert KnutDiego Priestly BOOK_PRICE 23.2512.6518.902.
Paper For Above instruction
This paper addresses the process of database normalization for a bookstore's sales tracking system, focusing on the design and refinement of entities using dependency diagrams. The core objective is to identify, analyze, and eliminate various types of dependencies in the data to ensure an efficient, non-redundant, and logically structured database that conforms to normalization standards. The discussion encompasses detailed steps for drawing dependency diagrams, identifying partial and transitive dependencies, removing them to attain higher normal forms, and ultimately creating a comprehensive Entity-Relationship Diagram (ERD) with Crow’s Foot notation, including primary and foreign key identification.
Introduction
Database normalization is crucial for establishing efficient and consistent data storage structures. It involves organizing data to reduce redundancy and dependency by decomposing tables into smaller, well-defined entities. This process typically involves several normal forms, each addressing specific types of anomalies caused by functional dependencies. In this context, the bookstore's sales tracking system must be structured to conform first to the First Normal Form (1NF), then progressing through Second (2NF), and Third Normal Form (3NF) for optimized data integrity. The initial data, derived from sample values, helps ascertain the nature of dependencies, guiding the normalization process and diagram constructions.
Part 1: Dependency Diagram and Identification of Dependencies
The initial task involved drawing a dependency diagram based on sample data from the bookstore's table. This table includes attributes such as BOOK_CODE, BOOK_TITLE, GENRE_CODE, GENRE_DESCRIP, AUTHOR_ID, AUTHOR_NAME, and BOOK_PRICE. Sample data reveal that the BOOK_CODE uniquely identifies each book yet is related to other attributes like BOOK_TITLE and BOOK_PRICE, implying a dependency of these attributes on BOOK_CODE. Additionally, GENRE_CODE determines GENRE_DESCRIP, indicating a functional dependency between genre code and its description. Similarly, AUTHOR_ID determines AUTHOR_NAME, establishing an Author entity relationship. The dependency diagram visualizes these relationships, illustrating how some attributes are partially dependent on composite keys and others are transitively dependent, which informs subsequent normalization steps.
Part 2: Removing Partial Dependencies and Achieving 2NF
Partial dependencies occur when non-prime attributes are functionally dependent on part of a composite primary key. To resolve this, the initial table was decomposed into smaller tables. For example, GENRE_CODE and GENRE_DESCRIP form a separate Genre table, isolating genre details. Likewise, AUTHOR_ID and AUTHOR_NAME constitute an Author table. The original table now primarily contains BOOK_CODE, BOOK_TITLE, GENRE_CODE, AUTHOR_ID, and BOOK_PRICE, with BOOK_CODE remaining as the primary key. This restructuring eliminates partial dependencies and elevates the design to Second Normal Form (2NF). The dependency diagram was updated accordingly to reflect these new relationships, emphasizing that attributes depending solely on the primary key are retained, while those depending on non-key attributes are moved to separate tables.
Part 3: Removing Transitive Dependencies and Achieving 3NF
The next phase involved eliminating transitive dependencies where non-prime attributes depend on other non-prime attributes. For instance, in the refined table, BOOK_PRICE depends on BOOK_CODE, and GENRE_DESCRIP depends on GENRE_CODE. To achieve Third Normal Form (3NF), the transitive dependency between GENRE_DESCRIP and GENRE_CODE was addressed by ensuring GENRE_DESCRIP resides solely within the Genre table. Similarly, AUTHOR_NAME depends on AUTHOR_ID, so it remains within the Author table. The final schema comprises normalized tables where each non-prime attribute is directly dependent on the primary key, with no transitive dependencies remaining. The dependency diagram was revised again, illustrating these clean relationships, and verification confirmed that all tables are in 3NF.
Part 4: Drawing the Fully Labeled Crow’s Foot ERD
The culmination of the normalization process is the creation of a comprehensive Entity-Relationship Diagram (ERD) using Crow’s Foot notation. The ERD includes entities such as Book, Genre, and Author, each with primary keys labeled distinctly. Relationships between these entities are clearly depicted, with one-to-many links annotated appropriately. Foreign keys are explicitly identified in each related entity; for example, the Book entity contains foreign keys GENRE_CODE and AUTHOR_ID referencing the Genre and Author tables respectively. The diagram provides a complete visual overview that encompasses all attributes, keys, and relationships, facilitating understanding of the data structure and serving as a foundation for database implementation.
Conclusion
The process of normalization, from initial dependency analysis through to ERD creation, enhances data integrity and reduces redundancy in the bookstore's sales tracking system. By methodically identifying and removing partial and transitive dependencies, the database design aligns with accepted normal forms, ensuring efficient data management. The final ERD serves as a crucial blueprint for implementation, supporting the bookstore’s operational needs while maintaining data consistency and scalability. This exercise demonstrates the vital importance of normalization and ERD development in effective database design, especially within retail environments where data accuracy and accessibility are paramount.