Q: Which column property would you use to require that a monetary amount in one column be less than another monetary amount in the same row (for example, discount_amount < total_amount)?

Introduction / Context: Relational databases can enforce business rules at the schema level. A common rule compares values across columns within the same row (for example, a discount cannot exceed the total). Given Data / Assumptions: The comparison is row-scoped (same row). We need a declarative way to enforce an inequality between two columns. Concept / Approach: Data constraints, typically a CHECK constraint, let you express rules such as discount_amount < total_amount. Data type defines format, null status controls presence, and default value provides a fallback value—none of those compare two columns. Step-by-Step Solution: Identify rule: one column must be less than another.Use a CHECK constraint to express the predicate (for example, CHECK (discount_amount <= total_amount)).Therefore, choose “Data constraints.” Verification / Alternative check: DBMS DDL shows CHECK constraints evaluating boolean expressions per row during INSERT/UPDATE. Why Other Options Are Wrong: Null status/Data type/Default value: None can enforce cross-column comparison by themselves. Common Pitfalls: Forgetting to consider NULL semantics (for example, when either column is NULL, the CHECK may evaluate to unknown and pass/fail depending on DBMS). Require NOT NULL if appropriate. Final Answer: Data constraints

Q: Which column(s) is/are strictly required in a properly designed relational table from a logical modeling perspective?

Introduction / Context: Every relation (table) should have a way to uniquely identify each row. This uniqueness requirement underpins keys, indexing, and referential integrity. Given Data / Assumptions: The question asks what is required in a table design. We are considering logical design best practice (and most physical implementations). Concept / Approach: A primary key is the designated candidate key that uniquely identifies each row. While a surrogate key is a common implementation of a primary key, it is not required specifically—natural keys can serve. Foreign keys and alternate keys are optional depending on relationships and additional uniqueness needs. Step-by-Step Solution: Recognize the core requirement: unique identification of rows.Map this to “primary key.”Pick “A primary key.” Verification / Alternative check: Normalization theory and most DBMS tools expect a primary key for each base table to ensure integrity and support indexing. Why Other Options Are Wrong: Foreign key: Only required if the table participates as child in a relationship. Alternate key: Useful but optional. Surrogate key: One way to implement a primary key, but not mandatory. Common Pitfalls: Assuming every primary key must be surrogate; sometimes a stable natural key is better. Final Answer: A primary key

Q: Which of the following statements is not true about surrogate keys in relational database design?

Introduction / Context: Surrogate keys are system-generated identifiers used as primary keys in relational databases. They are often used when no suitable natural key exists or when we want to keep business logic separate from technical identifiers. Given Data / Assumptions: Surrogate keys are typically numeric and auto-incremented. They are generated internally by the DBMS. The question asks which statement about surrogate keys is incorrect. Concept / Approach: Surrogate keys have no business meaning. They are purely artificial identifiers. They are usually short (e.g., integers), fixed (do not change once assigned), and numeric. The incorrect statement would be that they “have meaning to the user.” Step-by-Step Solution: List the properties of surrogate keys.Check each option against standard definitions.Identify the false statement as the one implying business meaning. Verification / Alternative check: Database theory literature confirms that surrogate keys are arbitrary identifiers with no semantic meaning in business terms. Why Other Options Are Wrong: They are short: Usually true since integers are compact. They are fixed: Once assigned, surrogate keys do not change. They are numeric: Generally implemented as integers or bigints. They have meaning to the user: False; they are meaningless to end users. Common Pitfalls: Assuming surrogate keys can encode business semantics; that is the role of natural keys. Final Answer: They have meaning to the user.

Q: In relational databases, if a relationship has a CASCADE UPDATE constraint, then if which key in the parent table is modified, the same change will automatically be made to all corresponding foreign key values in the child table?

Introduction / Context: Referential integrity constraints define how changes in one table affect related rows in another. The CASCADE UPDATE rule ensures consistency between parent and child rows when a parent key changes. Given Data / Assumptions: A parent-child relationship exists between two tables. The child table references the parent's primary key via a foreign key. A CASCADE UPDATE constraint has been set on the relationship. Concept / Approach: With CASCADE UPDATE, if the value of the parent's primary key changes, the DBMS automatically updates all foreign keys in child rows that reference it. This preserves referential integrity without manual intervention. Step-by-Step Solution: Define CASCADE UPDATE as applied to foreign keys.Identify which parent attribute it applies to: the referenced primary key.Confirm that foreign key values in child rows are updated accordingly. Verification / Alternative check: SQL standard and vendor documentation specify that CASCADE actions apply only to referenced primary key values. Why Other Options Are Wrong: Alternate key: Not normally referenced in foreign key definitions. Surrogate key: May be used as a primary key, but the rule applies because it is the primary key, not because it is a surrogate. Foreign key: Exists in the child table, not the parent. Common Pitfalls: Believing cascade applies to any key; it only applies to the referenced key in the parent table. Final Answer: the primary key

Question 1

ER Modeling Constraints — Covering Requirement for Ternary Relationships Which integrity constraint requires that the associated binary relationship(s) enumerate all combinations that must appear in a related ternary relationship (i.e., the ternary …

Accepted Answer

Introduction: Advanced entity–relationship (ER) modeling includes constraints that relate lower-degree (binary) relationships to higher-degree (ternary) ones. A covering constraint specifies how combinations in binaries correspond to combinations in a ternary association. This question asks you to name the constraint that requires full coverage of the ternary by the binaries. Given Data / Assumptions: We consider a ternary relationship among three entity types (for example, Supplier–Part–Project). Binary relationships may exist between each pair (Supplier–Part, Supplier–Project, Part–Project). The constraint may require that certain combinations present in binaries appear in the ternary. Concept / Approach: The MUST COVER constraint asserts that the specified binary relationships collectively cover all combinations that are required to exist in the ternary relationship. In other words, if a combination is indicated by the binaries under the constraint, it must also be present in the ternary set. This is different from a prohibition constraint (MUST NOT), which forbids certain combinations, and from weaker allowances that do not enforce coverage. Step-by-Step Solution: 1) Identify that the question seeks a constraint enforcing inclusion (coverage), not exclusion.2) Map “coverage” to the notion that the ternary must contain all combinations implied by binaries.3) Select MUST COVER as the named constraint that encodes this requirement. Verification / Alternative check: ER textbooks discussing higher-arity relationships describe covering and exclusion constraints to control permissible tuples in ternary associations. MUST COVER corresponds to required inclusion. Why Other Options Are Wrong: MUST NOT: Expresses exclusion, not required inclusion. Both of the above: Mutually inconsistent (coverage vs exclusion). None of the above / PARTIAL ALLOW: Do not name the required inclusion constraint. Common Pitfalls: Confusing participation constraints (total/partial participation) at the entity level with covering constraints relating binary and ternary relationships. Final Answer: MUST COVER

Question 2

In relational database design, what do we call a unique, DBMS-supplied identifier that is used as the primary key of a relation (table)?

Accepted Answer

Introduction / Context: A core decision in database schema design is how to identify each row uniquely. Sometimes natural keys (business keys) exist, but often designers choose system-generated identifiers. This question checks your understanding of that special type of key. Given Data / Assumptions: The identifier is supplied by the DBMS or application as an arbitrary unique value. It is used as the table’s primary key. It does not encode business meaning. Concept / Approach: A surrogate key is a meaningless, unique identifier (for example, an auto-increment integer or a UUID) created to serve as the primary key. It simplifies joins, avoids changes when business attributes evolve, and provides uniformity across tables. It contrasts with natural keys, which come from the domain (such as email or SKU) and carry meaning. Step-by-Step Solution: Identify the key as DBMS-supplied and unique.Note it is used as the primary key of the relation.Conclude that such a key is called a “surrogate key”. Verification / Alternative check: Many DBMSs support sequences, identity columns, or generated UUIDs precisely to implement surrogate keys cleanly and efficiently. Why Other Options Are Wrong: Primary key: Describes the role, not the nature; a surrogate key is a kind of primary key. Foreign key: References a primary key in another table. Composite key: Combines multiple columns; not necessarily DBMS-supplied or meaningless. Common Pitfalls: Believing a surrogate key must be numeric only; UUIDs are common too. Confusing “surrogate key” with “alternate key.” Final Answer: surrogate key

Question 3

In entity–relationship modeling, for any given relationship between two entities, how many possible sets of minimum cardinalities exist across the pair?

Accepted Answer

Introduction / Context: Cardinality in ER modeling expresses how many instances of one entity can or must relate to instances of another entity. Minimum cardinality captures the “optionality” requirement—whether participation is required (1) or optional (0). Given Data / Assumptions: Two entities participate in a relationship. Each side's minimum cardinality can be 0 (optional) or 1 (mandatory). Concept / Approach: For two entities A and B, each side has two possibilities for minimum cardinality: 0 or 1. The combination count equals the product of possibilities: 2 * 2 = 4. The four specific sets are (0,0), (0,1), (1,0), and (1,1). Step-by-Step Solution: List options for A: min(A) ∈ {0, 1}.List options for B: min(B) ∈ {0, 1}.Compute combinations: 2 * 2 = 4 → four possible sets. Verification / Alternative check: Any ER diagramming method that uses mandatory/optional marks per side implicitly supports these four cases. Why Other Options Are Wrong: Two/Three/Six: Do not cover all paired combinations of two binary choices. Common Pitfalls: Confusing minimum cardinality with maximum cardinality (1 or many). Minimum cardinality is about required participation, not quantity caps. Final Answer: Four

Question 4

Which data constraint specifies that values in a column must come from a defined, specific set (that is, only allowed values are permitted)?

Accepted Answer

Introduction / Context: Constraints enforce data quality by restricting what can be stored. Among them, domain constraints govern the permissible set of values at the attribute level. Given Data / Assumptions: We want to restrict a column to a particular allowed set (for example, status ∈ {'New', 'Open', 'Closed'}). The constraint applies to the attribute's legal values. Concept / Approach: A domain constraint defines the set of valid values for an attribute. It can be implemented with a CHECK constraint, an enumerated type, or a reference table with a foreign key. The key idea is that only listed or allowable values can exist in that column. Step-by-Step Solution: Recognize the requirement: whitelist of legal values.Map that to domain-level enforcement.Select “domain constraint”. Verification / Alternative check: DBMS documentation often shows domain checks as CHECK (status IN (...)) or by referencing a domain table. Why Other Options Are Wrong: Range constraint: Restricts by numeric/temporal range, not a discrete set. Intrarelation/Interrelation constraints: Describe constraints within or between tables generally; they do not specifically denote value-domain restrictions. Common Pitfalls: Hard-coding value lists across application tiers instead of centralizing in the database; forgetting to validate during updates as well as inserts. Final Answer: A domain constraint

Question 5

In relational databases, what is a foreign key best described as?

Accepted Answer

Introduction / Context: Foreign keys are the backbone of referential integrity. They link child tables to parent tables, ensuring relationships remain consistent over time. Given Data / Assumptions: We need the definition that characterizes a foreign key. Focus is on purpose and relational meaning. Concept / Approach: A foreign key is one or more columns in a child table whose values must match a candidate key (usually the primary key) in the parent table. This guarantees only existing parent rows can be referenced by the child. Step-by-Step Solution: Recall that FKs enforce referential integrity.They store key values from a parent table to represent relationships.Therefore, choose the option describing “contains the primary key of another table.” Verification / Alternative check: Any relational textbook or DBMS manual defines foreign keys this way; DDL syntax (FOREIGN KEY ... REFERENCES parent(col)) confirms it. Why Other Options Are Wrong: Data types / null status: These are column properties, not what a foreign key is. All of the above: Incorrect since only one statement accurately defines a foreign key. Common Pitfalls: Confusing logical FK concept with physical enforcement; some systems allow foreign keys to be deferred or not declared, but the concept remains the same. Final Answer: a column that contains the primary key value of another (parent) table

Question 6

When enforcing minimum cardinalities in a relationship between two entities, how many distinct types of actions must be considered overall?

Accepted Answer

Introduction / Context: Minimum cardinality expresses whether participation in a relationship is optional (0) or mandatory (1) for each entity. Enforcing these rules requires considering actions that occur on each side. Given Data / Assumptions: Two entities participate in one relationship. Each side may have a minimum of 0 or 1. We are looking for the types of actions to enforce these minima. Concept / Approach: To enforce minimum cardinality you must ensure compliance from the perspective of each entity type: (1) actions taken when creating or updating an instance of the first entity and (2) actions taken when creating or updating an instance of the second entity. In practice these are enforced via constraints, triggers, or application logic that check required related instances from both sides. Step-by-Step Solution: Recognize two enforcement perspectives: Entity A's required participation and Entity B's required participation.For each perspective, validate existence of required related rows at insert/update/delete time.Count distinct action types across sides → two overall. Verification / Alternative check: Design method guides often break enforcement by side: enforce "each A must have at least one B" and "each B must have at least one A" as separate checks. Why Other Options Are Wrong: Three/Four/Six: Overstates the number of fundamental enforcement directions; while there are many event points (insert/update/delete) the types collapse to two sides of the same relationship. Common Pitfalls: Confusing the number of minimum cardinality sets (four) with the number of enforcement directions (two). Also conflating minimum with maximum cardinality. Final Answer: Two

Question 7

Which column property in a relational table specifies whether cells must contain a value (that is, whether blanks are allowed)?

Accepted Answer

Introduction / Context: Every column definition includes properties that control the kind of data permitted and whether data is required. Knowing where “must have a value” is configured is fundamental to schema design. Given Data / Assumptions: The question asks which property enforces “value required.” We are not selecting the data type or a default value. Concept / Approach: Nullability (null status) controls whether NULLs are permitted. Declaring a column NOT NULL ensures every row must supply a value. This is different from data type (which sets format/precision) and default value (which supplies a value if one is omitted). Step-by-Step Solution: Identify requirement: mandatory presence of data.Map to NOT NULL / NULL property.Choose “Null status”. Verification / Alternative check: DDL examples: column_name data_type NOT NULL; enforced by the DBMS on INSERT/UPDATE. Why Other Options Are Wrong: Data type: Defines form, not presence. Default value: Supplies a value, but does not itself forbid NULL unless combined with NOT NULL. Data constraints: A broader category; nullability is specifically the null status. Common Pitfalls: Assuming a default value implies NOT NULL; it does not. You can still insert NULL unless NOT NULL is specified. Final Answer: Null status

Question 8

Which column property would you use to require that a monetary amount in one column be less than another monetary amount in the same row (for example, discount_amount < total_amount)?

Accepted Answer

Introduction / Context: Relational databases can enforce business rules at the schema level. A common rule compares values across columns within the same row (for example, a discount cannot exceed the total). Given Data / Assumptions: The comparison is row-scoped (same row). We need a declarative way to enforce an inequality between two columns. Concept / Approach: Data constraints, typically a CHECK constraint, let you express rules such as discount_amount < total_amount. Data type defines format, null status controls presence, and default value provides a fallback value—none of those compare two columns. Step-by-Step Solution: Identify rule: one column must be less than another.Use a CHECK constraint to express the predicate (for example, CHECK (discount_amount <= total_amount)).Therefore, choose “Data constraints.” Verification / Alternative check: DBMS DDL shows CHECK constraints evaluating boolean expressions per row during INSERT/UPDATE. Why Other Options Are Wrong: Null status/Data type/Default value: None can enforce cross-column comparison by themselves. Common Pitfalls: Forgetting to consider NULL semantics (for example, when either column is NULL, the CHECK may evaluate to unknown and pass/fail depending on DBMS). Require NOT NULL if appropriate. Final Answer: Data constraints

Question 9

Which column(s) is/are strictly required in a properly designed relational table from a logical modeling perspective?

Accepted Answer

Introduction / Context: Every relation (table) should have a way to uniquely identify each row. This uniqueness requirement underpins keys, indexing, and referential integrity. Given Data / Assumptions: The question asks what is required in a table design. We are considering logical design best practice (and most physical implementations). Concept / Approach: A primary key is the designated candidate key that uniquely identifies each row. While a surrogate key is a common implementation of a primary key, it is not required specifically—natural keys can serve. Foreign keys and alternate keys are optional depending on relationships and additional uniqueness needs. Step-by-Step Solution: Recognize the core requirement: unique identification of rows.Map this to “primary key.”Pick “A primary key.” Verification / Alternative check: Normalization theory and most DBMS tools expect a primary key for each base table to ensure integrity and support indexing. Why Other Options Are Wrong: Foreign key: Only required if the table participates as child in a relationship. Alternate key: Useful but optional. Surrogate key: One way to implement a primary key, but not mandatory. Common Pitfalls: Assuming every primary key must be surrogate; sometimes a stable natural key is better. Final Answer: A primary key

Question 10

Which of the following statements is not true about surrogate keys in relational database design?

Accepted Answer

Introduction / Context: Surrogate keys are system-generated identifiers used as primary keys in relational databases. They are often used when no suitable natural key exists or when we want to keep business logic separate from technical identifiers. Given Data / Assumptions: Surrogate keys are typically numeric and auto-incremented. They are generated internally by the DBMS. The question asks which statement about surrogate keys is incorrect. Concept / Approach: Surrogate keys have no business meaning. They are purely artificial identifiers. They are usually short (e.g., integers), fixed (do not change once assigned), and numeric. The incorrect statement would be that they “have meaning to the user.” Step-by-Step Solution: List the properties of surrogate keys.Check each option against standard definitions.Identify the false statement as the one implying business meaning. Verification / Alternative check: Database theory literature confirms that surrogate keys are arbitrary identifiers with no semantic meaning in business terms. Why Other Options Are Wrong: They are short: Usually true since integers are compact. They are fixed: Once assigned, surrogate keys do not change. They are numeric: Generally implemented as integers or bigints. They have meaning to the user: False; they are meaningless to end users. Common Pitfalls: Assuming surrogate keys can encode business semantics; that is the role of natural keys. Final Answer: They have meaning to the user.

Question 11

In relational databases, if a relationship has a CASCADE UPDATE constraint, then if which key in the parent table is modified, the same change will automatically be made to all corresponding foreign key values in the child table?

Accepted Answer

Introduction / Context: Referential integrity constraints define how changes in one table affect related rows in another. The CASCADE UPDATE rule ensures consistency between parent and child rows when a parent key changes. Given Data / Assumptions: A parent-child relationship exists between two tables. The child table references the parent's primary key via a foreign key. A CASCADE UPDATE constraint has been set on the relationship. Concept / Approach: With CASCADE UPDATE, if the value of the parent's primary key changes, the DBMS automatically updates all foreign keys in child rows that reference it. This preserves referential integrity without manual intervention. Step-by-Step Solution: Define CASCADE UPDATE as applied to foreign keys.Identify which parent attribute it applies to: the referenced primary key.Confirm that foreign key values in child rows are updated accordingly. Verification / Alternative check: SQL standard and vendor documentation specify that CASCADE actions apply only to referenced primary key values. Why Other Options Are Wrong: Alternate key: Not normally referenced in foreign key definitions. Surrogate key: May be used as a primary key, but the rule applies because it is the primary key, not because it is a surrogate. Foreign key: Exists in the child table, not the parent. Common Pitfalls: Believing cascade applies to any key; it only applies to the referenced key in the parent table. Final Answer: the primary key

Question 12

In relational database design, which column property should you choose to ensure that every cell in a column stores a monetary value (for example, prices in ₹ or $), with an appropriate numeric precision and scale?

Accepted Answer

Introduction / Context: When creating tables, one of the most important choices is the column's data type. For money-like values (such as prices, totals, taxes, and discounts), the data type determines how values are stored, their precision, and how arithmetic behaves. Choosing the right property avoids rounding errors and guarantees that each value is treated as numeric currency rather than as free text. Given Data / Assumptions: We are defining a column that must store monetary values (₹, $, or other currency units). We want predictable arithmetic and exact storage of decimals where possible. The database is a relational DBMS such as PostgreSQL, SQL Server, MySQL, or Oracle. Concept / Approach: The data type is the column property that enforces what kind of data can be stored. For currency, fixed-point numeric types (for example, DECIMAL(p,s) or NUMERIC(p,s)) are preferred because they support exact arithmetic with a defined precision (p) and scale (s). Other properties (NULL status, default values, constraints) refine behavior, but the foundational guarantee that a column holds monetary numbers comes from the data type. Step-by-Step Solution: Identify the requirement: store currency values accurately.Select a fixed-point numeric data type: DECIMAL or NUMERIC with appropriate precision/scale (for example, NUMERIC(12,2)).Optionally add CHECK constraints to enforce nonnegative values or maximum limits, and add a DEFAULT if needed.Document the unit (₹ or $) at the application or view layer to avoid ambiguity. Verification / Alternative check: Insert typical values (for example, 199.99, 0.05, 9999999.99) and perform arithmetic. Confirm that results are exact under DECIMAL/NUMERIC and that the DBMS prevents non-numeric input. Why Other Options Are Wrong: Null status: Controls presence/absence of a value, not whether it is monetary. Default value: Supplies an initial value but does not enforce numeric currency type. Data constraints: Helpful for ranges or positivity, but they complement, not replace, the data type. Collation: Applies to text sorting/comparison, irrelevant for numeric currency. Common Pitfalls: Using floating-point types (REAL/DOUBLE) for money can introduce rounding errors. Always choose fixed-point NUMERIC/DECIMAL for financial calculations. Final Answer: Data type

Question 13

You need to ensure, within a single row of the same table, that the value in one column is always less than the value in another column (for example, start_amount < end_amount). Which type of data constraint best enforces this rule?

Accepted Answer

Introduction / Context: Business rules often compare two columns in the same row, such as start_date before end_date or minimum_value less than maximum_value. Enforcing this rule in the database ensures integrity regardless of application code and prevents bad data from being stored. Given Data / Assumptions: The comparison is row-internal: ColumnA of a row must be less than ColumnB of the same row. We are working within a single table; no cross-table relationship is required. We want the DBMS to reject any row violating the rule. Concept / Approach: An intrarelation constraint (often implemented as a CHECK constraint) enforces relationships among columns within the same table row. For example: CHECK (start_amount < end_amount). In contrast, interrelation constraints involve two tables (such as foreign keys). Domain or range constraints restrict individual columns independently without referencing other columns. Step-by-Step Solution: Identify the rule: ColumnA must be less than ColumnB in the same row.Implement a CHECK constraint on the table: CHECK (ColumnA < ColumnB).Test by inserting valid and invalid rows to confirm enforcement. Verification / Alternative check: Attempt to insert a row with ColumnA >= ColumnB. The DBMS should raise an error, demonstrating that the intrarelation constraint works as intended. Why Other Options Are Wrong: Domain/range constraints: Apply to a single column's allowable values without comparing to another column. Interrelation constraint: Involves multiple tables, not needed here. Foreign key constraint: Ensures referential integrity across tables, not comparisons within one row. Common Pitfalls: For nullable columns, specify the intended behavior (for example, require NOT NULL or include logic such as CHECK (ColumnA IS NULL OR ColumnB IS NULL OR ColumnA < ColumnB)). Final Answer: An intrarelation constraint

Question 14

You want every new row to automatically start with a monetary value of $10,000 in a particular column unless the insert specifies another value. Which column property sets this initial monetary value?

Accepted Answer

Introduction / Context: Defaults improve data consistency by supplying a value when inserts omit a column. For monetary fields, setting a sensible default can streamline data entry and ensure predictable behavior across applications and ETL jobs. Given Data / Assumptions: A monetary column should initialize to $10,000 automatically. Applications may insert rows without explicitly setting this column. The DBMS supports column defaults (for example, DEFAULT in CREATE/ALTER TABLE). Concept / Approach: The default value column property supplies an automatic value when an INSERT omits the column. In SQL, you define it as DEFAULT 10000. It does not enforce that only 10,000 is allowed; it simply initializes the value. Data type still needs to be appropriate (for example, NUMERIC(12,2)), and constraints can further limit ranges or sign. Step-by-Step Solution: Choose a fixed-point numeric type suitable for currency (for example, NUMERIC(12,2)).Set DEFAULT 10000.00 on the column definition.Insert a row omitting the column and verify it populates with 10000.00. Verification / Alternative check: Select after insert and confirm the default value appears. Override by explicitly specifying a different amount in the INSERT and confirm it respects the provided value. Why Other Options Are Wrong: Null status: Controls presence/absence, not initialization. Data type: Ensures numeric format but does not set an initial value. Data constraints: Enforce rules (for example, nonnegative), not initialization. Identity/serial: Auto-generates surrogate keys, unrelated to currency defaults. Common Pitfalls: Assuming DEFAULT applies to updates—defaults are only used when the column is omitted in INSERT, not when it is set to NULL unless you also forbid NULLs. Final Answer: Default value

Question 15

During logical-to-physical mapping, the unique identifier of an entity in an ER model becomes which key in the relational table that represents that entity?

Accepted Answer

Introduction / Context: Entity-Relationship (ER) modeling captures real-world entities and their identifiers. When converting an ER model into relational tables, each entity becomes a table and its identifier becomes the table's primary key, ensuring row-level uniqueness and stable referencing from related tables. Given Data / Assumptions: An ER diagram defines entities with identifiers (natural or surrogate). We are mapping to a relational schema. We need stable, unique row identification and referential targets for relationships. Concept / Approach: The primary key uniquely identifies each row in the relational table that represents the entity. Relationships are implemented using foreign keys that reference these primary keys. Alternate keys can exist but are not the chosen primary key; identities/serials are one way to implement a surrogate primary key. Step-by-Step Solution: Identify the entity's identifier in the ER model.Implement that identifier as the table's PRIMARY KEY (possibly composite).Define foreign keys in related tables to reference this primary key. Verification / Alternative check: Confirm that the primary key prevents duplicates and provides a target for referential constraints from child tables. Why Other Options Are Wrong: Foreign key: Lives in a different (child) table and points to the primary key. Main attribute: Not a standard SQL term; ambiguous. Identity key: A mechanism for generating PK values, but not the conceptual mapping itself. Alternate key: A candidate key not chosen as the primary key. Common Pitfalls: Choosing a non-stable attribute (like mutable names) as the primary key can cause cascading updates. Prefer stable natural keys or surrogate keys as appropriate. Final Answer: primary key

Question 16

In transforming an ER model to a relational schema, each entity type is typically represented as which relational structure?

Accepted Answer

Introduction / Context: ER modeling precedes relational design. The standard mapping is straightforward: entities become tables; attributes become columns; and relationships become foreign keys (or associative tables). Understanding this mapping accelerates consistent, maintainable schemas. Given Data / Assumptions: An ER diagram defines one or more entity types with attributes. Target platform is a relational DBMS. We want a normalized first-cut schema. Concept / Approach: An entity becomes a table. Each table carries columns corresponding to the entity's attributes and a primary key that implements the entity's identifier. Relationships translate into foreign keys or, for many-to-many, into separate associative (junction) tables. Step-by-Step Solution: Enumerate entities in the ER model.Create a table for each entity with an appropriate primary key.Map attributes to columns and relationships to foreign keys or associative tables. Verification / Alternative check: Review that each table aligns to a single theme (3NF-friendly) and that all relationships are representable via keys. Why Other Options Are Wrong: Tuple: A tuple is a row, not an entire entity set. Attribute: Attributes become columns, not standalone entities. File: A storage concept outside relational modeling. View: A derived, virtual table; entities map to base tables. Common Pitfalls: Combining multiple entities in one table creates update anomalies. Keep one entity per table to maintain clarity and normalization. Final Answer: table

Question 17

In data modeling, which situations typically require using ID-dependent (identifying) entities whose primary keys include the parent’s key?

Accepted Answer

Introduction / Context: ID-dependent (identifying) entities are entities whose primary key includes the primary key of a parent entity. This modeling pattern expresses strong ownership and ensures a child cannot exist without its parent. It is useful in several recurring scenarios in logical design. Given Data / Assumptions: An identifying relationship implies the child’s PK includes the parent’s PK. We consider association entities, multivalued attributes, and archetype/instance structures. The target is a relational schema derived from an ER/EER model. Concept / Approach: Association (intersection) entities in many-to-many relationships often use a composite PK built from the parent PKs, making them ID-dependent on both parents. Multivalued attributes become separate child entities keyed by the parent's key plus a discriminator, thus ID-dependent. Archetype/instance patterns may use an identifying relationship to tie instances to their archetype via a composite identifier. Step-by-Step Solution: Identify ownership: the child makes no sense without the parent (for example, OrderLine depends on Order).Model the child’s PK to include the parent’s PK, forming an identifying (solid-diamond) relationship.For M:N associations, create an associative entity whose PK includes both parents’ PKs. Verification / Alternative check: Attempt to define the child without the parent key; if uniqueness breaks or orphan rows become possible, ID-dependence is indicated. Why Other Options Are Wrong: Options a/b/c each name a valid use, but not exclusively. The pattern applies to all of them. None of the above: Incorrect, as the scenarios listed are classic uses. Common Pitfalls: Overusing surrogate keys and losing the identifying tie. Even with a surrogate, keep a UNIQUE constraint on the natural identifying columns to preserve semantics. Final Answer: All of the above use ID dependent entities

Question 18

From a relational integrity perspective, how should a primary key be declared to ensure every row is uniquely and reliably identifiable?

Accepted Answer

Introduction / Context: The primary key is the cornerstone of relational design. It uniquely identifies each row and serves as the target for foreign keys. If a primary key could be NULL, it would fail to identify the row and break referential integrity assumptions. Given Data / Assumptions: Every table (except pure intersection tables using composite keys) should have a primary key. The DBMS enforces uniqueness and non-nullness for primary keys. NULL represents “unknown/absent,” which is incompatible with identity. Concept / Approach: A PRIMARY KEY constraint implicitly enforces NOT NULL and UNIQUE. If you define a composite primary key, every component is NOT NULL. This guarantees that each row has a fully populated identifier, enabling reliable joins and references. Step-by-Step Solution: Choose candidate key(s) that are stable and minimal.Declare PRIMARY KEY, which enforces NOT NULL automatically.For surrogate keys (IDENTITY/SERIAL/GENERATED), the same NOT NULL requirement applies. Verification / Alternative check: Attempting to insert a row with a NULL primary-key column should fail with a constraint violation, confirming enforcement. Why Other Options Are Wrong: NULL: Cannot uniquely identify a row; multiple NULLs would be ambiguous. Either of the above: Not acceptable; PK must be NOT NULL. None of the above: Incorrect because NOT NULL is required. DEFERRABLE: Relates to timing of constraint checking; PK non-nullness is not deferrable in standard practice. Common Pitfalls: Selecting mutable attributes as PKs can cause cascading updates. Prefer stable natural keys or surrogates. Final Answer: NOT NULL.

Question 19

For a one-to-one (1:1) relationship between two tables, where should the foreign key be placed to implement the relationship in the relational schema?

Accepted Answer

Introduction / Context: Unlike one-to-many relationships, a one-to-one (1:1) relationship offers flexibility in where you place the foreign key. The design choice depends on optionality, access patterns, and normalization goals. Given Data / Assumptions: Two tables are in a 1:1 relationship. Each row in Table A matches at most one row in Table B, and vice versa. You may have optional participation on one side (partial specialization). Concept / Approach: In a 1:1, the foreign key can reside in either table. A common approach is to place the FK in the table that is optional (the “child” in an identifying sense), possibly also making it the primary key (PK = FK) to enforce strict 1:1. If both sides are mandatory, choose the table that best fits access and lifecycle semantics. Step-by-Step Solution: Determine optionality: which side can exist without the other?Place the FK in the optional side and consider PK=FK to enforce true 1:1.Add UNIQUE constraints if necessary to prevent multiple matches. Verification / Alternative check: Attempt to insert multiple rows referencing the same counterpart; UNIQUE/PK=FK should prevent violations, confirming a true 1:1. Why Other Options Are Wrong: Parent-only or child-only as a rule: Overly rigid; correct placement depends on design. Either table without defining parent/child: You still need to define constraint semantics; “either without specifying” is vague. Separate junction table only: Junctions are for many-to-many, not necessary for 1:1. Common Pitfalls: Accidentally creating a 1:N by not enforcing uniqueness on the foreign key. Always ensure FK has a UNIQUE or PK constraint to maintain 1:1. Final Answer: either the parent table or the child table.

Question 20

For a one-to-many (1:N) relationship between Parent and Child tables, where is the foreign key placed to enforce the relationship?

Accepted Answer

Introduction / Context: One-to-many (1:N) relationships are core to relational modeling. The “many” side must reference the “one” side so that multiple children can point to the same parent while maintaining referential integrity. Given Data / Assumptions: The relationship is 1:N (for example, Customer → Orders). Each child row belongs to exactly one parent row. We want cascading behavior and integrity enforced in the database. Concept / Approach: The foreign key belongs in the child table (the N-side). It points to the parent’s primary key. This allows many child rows to reference one parent and enables DBMS enforcement of insert/update/delete rules (for example, ON DELETE RESTRICT or CASCADE). Step-by-Step Solution: Identify the parent (one) and child (many) tables.Add a foreign key column in the child referencing the parent’s primary key.Optionally index the foreign key for performance of joins and deletes. Verification / Alternative check: Attempt to insert a child with a nonexistent parent; the FK constraint should block it, confirming correct placement. Why Other Options Are Wrong: Parent table: Would imply many parents per child, which is backwards. Either table / junction table: Junction tables are for many-to-many, not 1:N. Either without specifying roles: Lacks necessary semantics and would not enforce 1:N properly. Common Pitfalls: Forgetting to add an index on the FK can slow deletions on the parent and joins. Consider ON DELETE behaviors based on business rules. Final Answer: the child table.

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