Data Normalisation Quiz

What is data normalization?

• The process of organizing data in a database to reduce redundancy and improve data integrity.

• The process of adding redundancy to data in a database

• The process of randomizing data in a database

• The process of deleting data from a database

What are the goals of data normalization?

• Increase data redundancy, worsen data integrity, and maximize data anomalies

• Reduce data redundancy, improve data integrity, and minimize data anomalies

• Maintain data redundancy, ignore data integrity, and encourage data anomalies

• Eliminate data redundancy, have no impact on data integrity, and maximize data anomalies

Explain the process of data normalization.

• Data normalization involves organizing data in a database to reduce redundancy and improve data integrity.

• Data normalization involves making data more complex and difficult to access.

• Data normalization has no impact on data integrity and redundancy.

• Data normalization is the process of adding redundancy to the database.

What are the different normal forms in data normalization?

• Basic normal form (BNF), Advanced normal form (ANF), Ultimate normal form (UNF)

• Primary normal form (PNF), Secondary normal form (SNF), Tertiary normal form (TNF)

• Simple normal form (SNF), Complex normal form (CNF), Complete normal form (CNF)

• First normal form (1NF), Second normal form (2NF), Third normal form (3NF), Boyce-Codd normal form (BCNF), and Fourth normal form (4NF)

What is the purpose of removing repeating groups in data normalization?

• To save storage space and improve data accuracy.

• To reduce data redundancy and improve data integrity.

• To make the data more confusing and difficult to understand.

• To increase data redundancy and decrease data integrity.

Why is it important to eliminate partial dependencies in data normalization?

• To slow down data retrieval and processing.

• To complicate the data structure.

• To avoid data redundancy and inconsistency.

• To increase data redundancy and inconsistency.

What is the role of functional dependencies in data normalization?

• Functional dependencies have no role in data normalization

• Functional dependencies only apply to non-relational databases

• Functional dependencies are used to create redundancy in the database

• Functional dependencies help in identifying the relationships between attributes in a database table.

Explain the concept of transitive dependencies in data normalization.

• Transitive dependencies occur when a prime attribute is functionally dependent on another prime attribute.

• Transitive dependencies occur when a non-prime attribute is functionally dependent on another non-prime attribute.

• Transitive dependencies occur when a non-prime attribute is not functionally dependent on any other attribute.

• Transitive dependencies occur when a non-prime attribute is functionally dependent on a composite key.

What are the advantages of data normalization?

• None of the above

• Increases redundancy

• Complicates data retrieval

• All of the above

How does data normalization help in reducing data redundancy and inconsistency?

• By adding more duplicate data

• By organizing data into tables and eliminating duplicate data.

• By randomly shuffling the data

• By storing data in unorganized files