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National University of Computer and Emerging Sciences Database Systems Quiz # 4 (Functional Dependency & Normalization) Name: Roll#: Date: Marks: 15 Q1. Consider the closure of the following set F

How to fill out functional dependency amp normalization

How to fill out functional dependency & normalization:

1. Identify the functional dependencies: Analyze the given data and determine the relationships between different attributes. This involves identifying dependencies where the value of one attribute determines the value of another attribute.
2. Normalize the data: Normalize the data by breaking it down into smaller tables to eliminate redundancy and improve data integrity. You can use normalization rules like first normal form (1NF), second normal form (2NF), and third normal form (3NF) to achieve this.
3. Apply normalization rules: Follow the normalization rules to ensure that each attribute in a table depends only on the primary key of that table. This helps in organizing the data efficiently and avoiding data anomalies.
4. Eliminate transitive dependencies: Identify and eliminate transitive dependencies, which occur when an attribute depends on another attribute that is not a primary key. This can be done by breaking down the table into smaller tables.
5. Perform normalization checks: Verify that the normalized tables satisfy the normalization rules. Ensure that there are no repeating groups, partial dependencies, or transitive dependencies present.

Who needs functional dependency & normalization?

1. Database Administrators: Database administrators play a crucial role in designing, managing, and optimizing databases. They need to understand functional dependency and normalization to ensure efficient storage, retrieval, and manipulation of data in the database.
2. Data Analysts: Data analysts work with large datasets to extract valuable insights and patterns. Understanding functional dependency and normalization helps them in managing and manipulating data effectively, which leads to accurate analysis and meaningful conclusions.
3. Software Developers: Software developers often work with databases and need to design schemas and optimize the performance of database operations. Having knowledge of functional dependency and normalization helps them in creating efficient and scalable database structures.
4. Data Scientists: Data scientists rely on structured and organized data to build models, perform statistical analysis, and make data-driven decisions. Understanding functional dependency and normalization ensures that the data used for analysis is accurate, reliable, and consistent.
5. Students of Database Management: Students studying database management or related fields need to learn about functional dependency and normalization as they form the foundation of database design and optimization. Mastering these concepts is essential for their academic and professional growth in the field of database management.

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What is functional dependency amp normalization?

Functional dependency is a relationship that exists between attributes in a database. Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity.

Who is required to file functional dependency amp normalization?

Database administrators, data analysts, and anyone responsible for managing a database are required to file functional dependency amp normalization.

How to fill out functional dependency amp normalization?

Functional dependency and normalization can be filled out by analyzing the relationships between attributes in a database and organizing the data to meet normalization standards.

What is the purpose of functional dependency amp normalization?

The purpose of functional dependency and normalization is to improve data integrity, reduce redundancy, and make data management more efficient.

What information must be reported on functional dependency amp normalization?

Information such as attribute relationships, data organization, and compliance with normalization standards must be reported on functional dependency and normalization.