Chapter 6: Normalization and Denormalization

Using an ER diagram can be helpful in designing a normalized schema because: A. the standard mapping of an ER diagram to a relational model always results in a normalized schema B. the process of mapping an ER diagram to a relational model is equivalent to the synthesis method of normalization C. the standard mapping of an ER diagram to a relational model results in a schema that is close to normalized

C. the standard mapping of an ER diagram to a relational model results in a schema that is close to normalized Higher Normal Forms

The normalization process that starts with a universal relation and uses decomposition to produce a set of normalized relations is called: A. analysis B. synthesis C. abstraction D. classification

A. analysis Higher Normal Forms

A relation is in _____ normal form if, and only if, every attribute is single-valued for each tuple. A. first B. second C. third D. Boyce-Codd

A. first Normalization Using Candidate Keys

A functional dependency in which the attributes on the right-hand side are included in the determinant is called: A. redundant B. normal C. trivial D. multi-valued

C. trivial Functional Dependency (FD)

Removing multi-valued dependencies is required for which normal form? A. 1NF B. 2NF C. 3NF D. 4NF

D. 4NF Higher Normal Forms

In a functional dependency, any attribute on the right side of the arrow is said to be: A. a determinant B. a superkey C. an independent attribute D. a dependent attribute

D. a dependent attribute Functional Dependency (FD)

A relation is first normal form is: A. every attribute is single-valued for each tuple B. the domains of the attributes are atomic C. each cell of the table can contain only one value D. all of these are correct

D. all of these are correct Normalization Using Candidate Keys

In relational decomposition of a universal relation, the property of dependency preservation requires that: A. all determinants appear in the same relation B. all attributes appear in some relations C. it is possible to reconstruct the original relation by a join D. all the attributes on both sides of each dependency appear in the same relation

D. all the attributes on both sides of each dependency appear in the same relation Properties of Relational Decompositions

All of the following are reasons for leaving a schema in a lower normal form except: A. desire to keep related items together in the same relation B. performance requirements C. desire to preserve functional dependencies in the same relation D. desire to reduce replication

D. desire to reduce replication The Normalization Process

In the relational model, a spurious tuple is one that: A. appears in the original relation B. does not have a candidate key C. has repeating values for an attribute D. does not appear in the original relation

D. does not appear in the original relation Properties of Relational Decomposition

In the relational model, every determinant is always: A. a candidate key B. a superkey C. a composite key D. none of these is correct

D. none of these is correct Functional Dependency (FD)

In the relational model, a projection is lossless if: A. the join produces the same structure as the original relation B. no further decomposition is possible C. the intersection of the relations is empty D. the join produces the same tuples as the original relation

D. the join produces the same tuples as the original relation Properties of Relational Decompositions

If set S{A, B, C} is a superkey for the relation R(A, B, C, D, E), then: A. {A, B} is also a superkey for R B. no subset of S is also a superkey for R C. {D, E} is also a superkey for R D. {A, B, C, D} is also a superkey for R

D. {A, B, C, D} is also a superkey for R. Superkeys, Candidate Keys, and Primary Keys

The standard decomposition algorithm for BCNF requires: A. identifying and removing each violation of BCNF from a universal relation B. normalizing 1NF, 2NF, and 3NF before normalizing BCNF C. grouping together FDs that have the same determinant D. mapping relations from and ER diagram

A. identifying and removing each violation of BCNF from a universal relation Properties of Relational Decompositions

It is always possible to find a Boyce-Codd Normal Form decomposition that: A. is lossless, but may not preserve dependencies B. preserves dependencies, but may not be lossless C. is both lossless and dependency-preserving D. is disjoint

A. is lossless, but may not preserve dependencies Properties of Relational Decompositions

For a relational decomposition, the property of being able to get back exactly the original relation by joins is: A. lossless decompostion B. dependency preservation C. attribute preservation D. relation preservation

A. lossless decomposition Properties of Relational Decompositions

If a relation is 3NF but not BCNF, it must have a non-trivial functional dependency X -> A such that: A. the primary key does not determine X B. X is not a superkey C. A is not a superkey D. the primary key does not determine A

B. X is not a superkey Normalization Using Candidate Keys

Which of the following is not one of the major objectives of normalization? A. removing redundancy B. improving efficiency C. removing anomalies D. increasing model flexibility

B. improving efficiency Objectives of Normalization

A prime attribute is one that is: A. part of a superky B. part of a candidate key C. a primary key D. a minimal identifier

B. part of a candidate key Functional Dependency (FD)

Examining an instance of a relation can be sufficient to prove: A. that it is in 3NF B. that it is not in 3NF C. that it contains a functional dependency D. that it contains a transitive dependency

B. that it is not in 3NF Insertion, Update, and Deletion Anomalies

The highest normal form that always allows us to preserve functional dependencies is: A. 1NF B. 2NF C. 3NF D. BCNF

C. 3NF Properties of Relational Decompositions

In the relation R(A, B, C, D) if D is multivalued and the apparent key is A, which of the following is not an acceptable way to create a first normal form table for this schema? A. Decompose R into R1(A, B, C) and R2(A, D) B. Determine n, the maximum number of values that there are for D in any record, and include that many columns for D, making the relation have the form R1(A, B, C,D1, D2, ... ,Dn). C. Decompose R into R1(A, B, C, D) and R2 (B, D) D. Use D as part of the primary key, making the relation have the form R1(A, D, B, C)

C. Decompose R into R1(A, B, C, D) and R2(B, D) Superkeys, Candidate Keys, and Primary Keys

A relation is second normal form if it is 1NF and: A. every attribute is single-valued B. every attribute is determined by a portion of the key C. every nonkey attribute is dependent on the entire key D. no nonkey attribute determines another

C. every nonkey attribute is dependent on the entire key Normalization Using Candidate Keys

The three types of dependencies involved in normalization are: A. functional, multivalued, and union B. functional, join, and union C. functional, join, and multivalued D. functional, integral, and multivalued

C. functional, join, and multivalued Insertion, Update, and Deletion Anomalies

If X and Y are attributes of relation R, and X functionally determines Y, the relationship from X to Y is: A. one-to-one B. one-to-many C. many-to-one D. many-to-many

C. many-to-one Functional Dependency (FD)