Data Management (Foundations) D426

Correct Answer

B. whole numbers

Explanation

The int data type is used to store whole numbers, also known as integers. It can represent positive, negative, and zero values, but it does not support fractional or decimal values. Integers are used for counting or indexing purposes.

Why other options are wrong

A. dates

The int data type cannot store dates. Dates are typically stored using a date or datetime data type, which is specifically designed for representing time-related data.

C. true or false values

True or false values are usually represented by the BOOLEAN data type or as integers (0 for false and 1 for true), not the int data type.

D. floating point numbers

Floating point numbers are stored using data types like FLOAT or DOUBLE. The int data type does not store fractional or decimal values, so it is not suitable for floating point numbers.

Correct Answer:

composite

Explanation:

When no single column can uniquely identify a record, multiple columns can be combined to form a composite key. This ensures that the combination of values across these columns uniquely identifies each row. Composite keys are widely used in relational database design, especially in junction tables that model many-to-many relationships. They maintain data integrity while avoiding duplication.

Why Other Options Are Wrong:

joined

Although it sounds related, "joined" is not the correct term in database terminology for a key made up of multiple columns. Joins are operations used to combine rows from different tables, not to define keys.

aggregate

Aggregate refers to functions like SUM, AVG, COUNT, etc., which perform calculations on sets of values. It has no relation to primary or candidate keys in database design, so this is an incorrect option.

union

Union is an SQL set operator used to combine results from two queries. It does not refer to key structures and cannot uniquely identify rows within a single table. Therefore, it is not the right choice.

Correct Answer

D. The SELECT-clause can include attributes of the relations listed in the FROM-clause not listed in the GROUP BY-clause.

Explanation

In SQL, when using aggregate functions with the GROUP BY clause, all non-aggregated columns listed in the SELECT clause must be included in the GROUP BY clause. If you try to select a column in the SELECT clause that is neither part of an aggregate function nor listed in the GROUP BY clause, it will result in an error. This ensures that each row in the result corresponds to a valid grouping of data.

Why other options are wrong

A. Aggregate functions include COUNT, SUM, AVG, MAX, and MIN.

This is correct. These are standard aggregate functions in SQL that operate on a set of rows and return a single value representing the summary of that set.

B. GROUP BY clause specifies the grouping attributes.

This is correct. The GROUP BY clause is used to group rows based on specified columns so that aggregate functions can be applied to each group.

C. The functions can be applied to each subgroup independently.

This is correct. Aggregate functions can be applied to each subgroup of data created by the GROUP BY clause, providing results specific to each group.

Correct Answer

B. many

Explanation

In a one-to-many relationship, the foreign key is placed in the table on the "many" side of the relationship. This is because the foreign key is used to reference the primary key in the table on the "one" side, establishing the relationship between the two tables. For example, in a relationship where one department can have many employees, the foreign key (department ID) will be placed in the employee table.

Why other options are wrong

A. weak

A weak entity is one that cannot be uniquely identified without the help of another entity. Weak entities are not relevant to the placement of foreign keys in a one-to-many relationship.

C. many-to-many

In a many-to-many relationship, a junction table is typically used to represent the relationship, which contains foreign keys referencing both related tables. The foreign key does not reside on just one side in a many-to-many relationship but is instead distributed across the junction table.

D. one

In a one-to-many relationship, the foreign key is placed in the table on the "many" side, not the "one" side. The "one" side will have the primary key, which is referenced by the foreign key on the "many" side.

E. cardinal

Cardinal refers to the cardinality of the relationship (such as one-to-many or many-to-many), not to the location of the foreign key in a one-to-many relationship.

Correct Answer:

Create a composite key through a formula field to be used as a primary key.

Explanation:

When no single field uniquely identifies each row in a dataset, combining multiple columns into a composite key ensures uniqueness. A composite key is formed by using two or more fields together to create a unique identifier. This approach aligns with relational database design principles, ensuring data integrity while allowing the table to maintain proper indexing and referencing. It avoids guesswork or external tools and follows accepted database normalization practices.

Why Other Options Are Wrong:

Add a randomly generated number for each line and use machine learning to help identify key matches.

Randomly generated numbers can introduce inconsistencies and are not tied to the inherent data. Machine learning is unnecessary for simple relational database design and does not guarantee consistent uniqueness. This option overcomplicates the problem and does not follow standard practices.

Remove this data as it is not useful.

Discarding data simply because it lacks a single natural key is wasteful. Many valuable datasets can still be used effectively by creating composite keys. Eliminating data disregards possible insights and is not a valid database design solution.

Use Machine Learning to identify what should be the primary key.

Machine learning is not designed to identify relational primary keys. It may find patterns, but it cannot enforce strict database-level uniqueness. Using ML for this purpose is impractical, inefficient, and contrary to established database design methods.

Correct Answer

 A. Analysis, logical design, physical design

Explanation

The process of converting an entity-relationship (ER) model into a functional database follows a sequence of three steps:

Analysis: The first step involves gathering requirements and understanding the data needs of the system. This step defines what needs to be modeled and how the database will function.

Logical design: The second step focuses on translating the ER model into a logical structure, usually involving the creation of tables, relationships, and other database objects.

Physical design: The final step involves determining how the database will be physically implemented in terms of storage, indexing, and performance optimization.

Why other options are wrong

 B. Physical design, logical design, analysis

 This order is incorrect because analysis must come before both logical and physical design. Without understanding the requirements (analysis), the logical and physical designs cannot be accurately created.

C. Logical design, analysis, physical design

 This order is incorrect because logical design should come after analysis, not before. You need to analyze the requirements first before creating the logical design.

D. Analysis, physical design, logical design

 This order is incorrect because physical design should come after logical design. The logical structure needs to be defined before determining how it will be physically implemented.

Correct Answer:

Box

Explanation:

In an entity-relationship (ER) diagram, entities are represented using rectangular boxes. Each box represents a distinct object or concept, such as Student or Course, and contains attributes that describe the entity. The box symbol clearly differentiates entities from relationships, which use other symbols such as diamonds or lines. This standard representation helps maintain clarity and consistency in database modeling.

Why Other Options Are Wrong:

Circle

Circles are not used to represent entities. In some ER notations, circles or ovals denote attributes, not entities. Using a circle for an entity would cause confusion and break ER diagram conventions.

Crow's Foot

Crow’s Foot notation represents relationships and cardinality (e.g., one-to-many). It is not used for entities themselves. Entities must be defined as boxes, and crow’s feet are attached to relationship lines only.

Crossbar

A crossbar in Crow’s Foot notation represents the "one" side of a relationship. It indicates constraints on cardinality, not an entity. Therefore, it cannot represent an entity in an ER diagram.

Line

Lines in ER diagrams show relationships or connections between entities. They are not used as symbols for entities themselves. Without boxes, it would be impossible to identify or define the entities clearly.

Correct Answer:

Equijoin

Explanation:

The query uses an INNER JOIN with a condition that matches rows based on equality (Employee.DeptID = Department.ID). A join based on equality is specifically called an equijoin. Since INNER JOINs are the most common form of equijoins, this query falls under that category. It retrieves only rows with matching department IDs in both tables.

Why Other Options Are Wrong:

Outer join

An outer join returns unmatched rows from one or both tables along with matched rows. The query shown uses INNER JOIN, not OUTER JOIN, so this is incorrect.

Self join

A self join is when a table is joined with itself to compare rows within the same table. Here, two different tables (Employee and Department) are being joined, not a single table with itself.

Cross join

A cross join produces the Cartesian product of two tables without any condition. Since the query uses a condition (Employee.DeptID = Department.ID), this is not a cross join.

Correct Answer

B. physical design

Explanation

Physical design is the phase where the actual implementation details of a database are planned out. This includes deciding on storage structures, indexing, and access methods. It takes into consideration the limitations, features, and performance characteristics of the specific Database Management System (DBMS) being used.

Why other options are wrong

A. logical design

Logical design focuses on the structure of the data and relationships between the data elements, but it remains independent of any specific DBMS. It doesn't account for system limitations or how the data will be physically stored or accessed. Therefore, while it is a crucial step, it is not the stage that considers DBMS-specific characteristics.

C. normalization

Normalization is a process used during logical design to reduce data redundancy and improve data integrity. It involves organizing the fields and tables of a database. However, it does not involve system-specific limitations or physical storage concerns, making it distinct from physical design.

D. conceptual design

Conceptual design represents the high-level structure of the database, focusing on the requirements and entities without concern for how the system will be implemented. It is even more abstract than logical design and thus does not account for DBMS-specific features or limitations.