WGU C175/D426 DATA MANAGEMENT
FOUNDATIONS OA. EXAM QUESTIONS
AND ANSWERS | 2026 UPDATE | 100%
CORRECT.
What does Modality refers to? How does it appear on ER diagram? - ANS Refers to the
MINIMUM number of times an instance in one entity can be associated with instance of
another entity (minima). Appears as a 0 or 1 on the relationship line, next to cardinality.
Define: Referential Integrity - ANS Requires that ALL foreign key values must either be fully
NULL or match some primary key value.
4 Ways Referential Integrity can be violated - ANS 1. Primary key is updated 2. Foreign key is
updated 3. Row containing primary key is DELETED 4. Row containing foreign key is INSERTED.
Actions to Correct Referential Integrity Violation - ANS 1. RESTRICT - rejects an insert, update,
or delete 2. SET NULL - sets invalid foreign keys to null 3. SET DEFAULT - sets invalid foreign keys
to a default primary value 4. CASCADE - propagates primary key changes to foreign keys.
What is an Important aspect of Referential Integrity - ANS Reference to data in one relation is
based on values in another relation.
What is Broad definition of data - ANS Raw facts captured on printed or digital media.
What Data - ANS Facts that are collected and stored in a database system.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 1 OF 31
,Determining characteristic of unstructured data - ANS It does not follow a data model.
Flat files - ANS They contain no internal hierarchical organization.
Data retrieval before database management systems - ANS Sequentially from simple files.
Primary Key - ANS An attribute or group of attributes that uniquely identify a tuple in a
relation.
Foreign Key matching - ANS A domain of values is necessary for a primary key in one relation
of a database to match with its corresponding foreign key in another relation of the same
database.
Alternate Key - ANS What uniquely identifies each entity in a collection of entities but is not
the primary key.
Candidate Key - ANS A set of columns in a table that can uniquely identify any record in that
table without referring to other data.
Database indexing - ANS The original data is copied to the index.
Indexes in physical database design - ANS To retrieve data DIRECTLY using a pointer.
Index creation on a database column - ANS To optimize data retrievals.
Functional Dependency - ANS Each value of a column relates to at MOST one value of
another column.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 2 OF 31
,Rules/Appearance of First Normal Form - ANS - All non-key columns depend on primary key -
Each table cell contains one value - A table with no duplicate rows.
Rules/Appearance of Second Normal Form - ANS - When all non-key columns depend on the
WHOLE primary key - Must be in 1NF - Non-key column can not depend on just one part of a
composite key - a single primary key is automatically in 2NF.
Rules/Appearance of Third Normal Form - ANS - All non-key columns depend ONLY on the
primary key - Tables are totally free of data redundancy.
Differences between operational and analytical databases - ANS - Volatility - Detail - Scope -
History.
Volatility - ANS Database updates in real time. Operational Data is Volatile. Analytical Data is
NOT Volatile.
Detail in databases - ANS - A database that keeps record of individual transactions; line items
- Operational: Detailed - Analytical: Detailed.
Scope in databases - ANS - How far a database can reach - Operational: incompatible -
Analytical: Enterprise-Wide/Summary.
History in databases - ANS - Whether DB is current or tracks all data - Operational: Current
only - Analytical: Tracks trends.
Data warehouse refresh process - ANS 1. Extraction 2. Cleanse 3. Integrate 4. Restructure 5.
Load.
Extraction in ETL - ANS Data extracted and put into staging area.
Cleanse in ETL - ANS Errors are eliminated from data; standard abbreviations applied.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 3 OF 31
, Integrate in ETL - ANS Data is put into a uniform structure; Data converted to uniform
structure.
Restructure in ETL - ANS Data is structured in a design that is optimal for analysis.
Load in ETL - ANS Data is loaded to the data warehouse.
Issue focused on 'Load' component of ETL - ANS Monitor refreshing volume and frequency.
Step in ETL Process where raw data is aggregated - ANS Transformation steps.
Data mining activities - ANS 1. Clustering & Segmentation 2. Classification 3. Estimation 4.
Prediction 5. Affinity Grouping 6. Description.
Clustering & Segmentation - ANS Taking large entity and dividing into smaller groups of
entities. Useful when unsure of what looking for.
Classification (Data Mining) - ANS Organizing data into predefined classes.
Estimation (Data Mining) - ANS Assigning a numeric value to an object.
Prediction (Data Mining) - ANS Classifying objects according to an expected future behavior.
Affinity Grouping - ANS Evaluating relationships between data elements that demonstrate
some kind of affinity between objects.
Entity types - ANS The uniquely identifiable element about which data can be categorized in
an entity-relationship diagram.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 4 OF 31
FOUNDATIONS OA. EXAM QUESTIONS
AND ANSWERS | 2026 UPDATE | 100%
CORRECT.
What does Modality refers to? How does it appear on ER diagram? - ANS Refers to the
MINIMUM number of times an instance in one entity can be associated with instance of
another entity (minima). Appears as a 0 or 1 on the relationship line, next to cardinality.
Define: Referential Integrity - ANS Requires that ALL foreign key values must either be fully
NULL or match some primary key value.
4 Ways Referential Integrity can be violated - ANS 1. Primary key is updated 2. Foreign key is
updated 3. Row containing primary key is DELETED 4. Row containing foreign key is INSERTED.
Actions to Correct Referential Integrity Violation - ANS 1. RESTRICT - rejects an insert, update,
or delete 2. SET NULL - sets invalid foreign keys to null 3. SET DEFAULT - sets invalid foreign keys
to a default primary value 4. CASCADE - propagates primary key changes to foreign keys.
What is an Important aspect of Referential Integrity - ANS Reference to data in one relation is
based on values in another relation.
What is Broad definition of data - ANS Raw facts captured on printed or digital media.
What Data - ANS Facts that are collected and stored in a database system.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 1 OF 31
,Determining characteristic of unstructured data - ANS It does not follow a data model.
Flat files - ANS They contain no internal hierarchical organization.
Data retrieval before database management systems - ANS Sequentially from simple files.
Primary Key - ANS An attribute or group of attributes that uniquely identify a tuple in a
relation.
Foreign Key matching - ANS A domain of values is necessary for a primary key in one relation
of a database to match with its corresponding foreign key in another relation of the same
database.
Alternate Key - ANS What uniquely identifies each entity in a collection of entities but is not
the primary key.
Candidate Key - ANS A set of columns in a table that can uniquely identify any record in that
table without referring to other data.
Database indexing - ANS The original data is copied to the index.
Indexes in physical database design - ANS To retrieve data DIRECTLY using a pointer.
Index creation on a database column - ANS To optimize data retrievals.
Functional Dependency - ANS Each value of a column relates to at MOST one value of
another column.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 2 OF 31
,Rules/Appearance of First Normal Form - ANS - All non-key columns depend on primary key -
Each table cell contains one value - A table with no duplicate rows.
Rules/Appearance of Second Normal Form - ANS - When all non-key columns depend on the
WHOLE primary key - Must be in 1NF - Non-key column can not depend on just one part of a
composite key - a single primary key is automatically in 2NF.
Rules/Appearance of Third Normal Form - ANS - All non-key columns depend ONLY on the
primary key - Tables are totally free of data redundancy.
Differences between operational and analytical databases - ANS - Volatility - Detail - Scope -
History.
Volatility - ANS Database updates in real time. Operational Data is Volatile. Analytical Data is
NOT Volatile.
Detail in databases - ANS - A database that keeps record of individual transactions; line items
- Operational: Detailed - Analytical: Detailed.
Scope in databases - ANS - How far a database can reach - Operational: incompatible -
Analytical: Enterprise-Wide/Summary.
History in databases - ANS - Whether DB is current or tracks all data - Operational: Current
only - Analytical: Tracks trends.
Data warehouse refresh process - ANS 1. Extraction 2. Cleanse 3. Integrate 4. Restructure 5.
Load.
Extraction in ETL - ANS Data extracted and put into staging area.
Cleanse in ETL - ANS Errors are eliminated from data; standard abbreviations applied.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 3 OF 31
, Integrate in ETL - ANS Data is put into a uniform structure; Data converted to uniform
structure.
Restructure in ETL - ANS Data is structured in a design that is optimal for analysis.
Load in ETL - ANS Data is loaded to the data warehouse.
Issue focused on 'Load' component of ETL - ANS Monitor refreshing volume and frequency.
Step in ETL Process where raw data is aggregated - ANS Transformation steps.
Data mining activities - ANS 1. Clustering & Segmentation 2. Classification 3. Estimation 4.
Prediction 5. Affinity Grouping 6. Description.
Clustering & Segmentation - ANS Taking large entity and dividing into smaller groups of
entities. Useful when unsure of what looking for.
Classification (Data Mining) - ANS Organizing data into predefined classes.
Estimation (Data Mining) - ANS Assigning a numeric value to an object.
Prediction (Data Mining) - ANS Classifying objects according to an expected future behavior.
Affinity Grouping - ANS Evaluating relationships between data elements that demonstrate
some kind of affinity between objects.
Entity types - ANS The uniquely identifiable element about which data can be categorized in
an entity-relationship diagram.
@COPYRIGHT ALL RIGHTS RESERVED PAGE 4 OF 31
