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Exam (elaborations)

WGU C175 OR D426 DATA MANAGEMENT FOUNDATIONS OA EXAM (2025) COMPLETE QUESTIONS WITH 100% VERIFIED SOLUTIONS

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Modality - 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. Referential Integrity - Requires that ALL foreign key values must either be fully NULL or match some primary key value. Ways Referential Integrity can be violated - 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 - 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. Important aspect of Referential Integrity - Reference to data in one relation is based on values in another relation. Broad definition of data - Raw facts captured on printed or digital media. Data - Facts that are collected and stored in a database system. Determining characteristic of unstructured data - It does not follow a data model. Flat files - They contain no internal hierarchical organization. Data retrieval before database management systems - Sequentially from simple files. Primary Key - An attribute or group of attributes that uniquely identify a tuple in a relation. Foreign Key matching - 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 - What uniquely identifies each entity in a collection of entities but is not the primary key. Candidate Key - A set of columns in a table that can uniquely identify any record in that table without referring to other data. Database indexing - The original data is copied to the index.

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WGU C175 OR D426 DATA
MANAGEMENT FOUNDATIONS OA
EXAM (2025) COMPLETE QUESTIONS
WITH 100% VERIFIED SOLUTIONS
Modality - 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.


Referential Integrity - Requires that ALL foreign key values must either be fully NULL
or match some primary key value.


Ways Referential Integrity can be violated - 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 - 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.


Important aspect of Referential Integrity - Reference to data in one relation is based on
values in another relation.


Broad definition of data - Raw facts captured on printed or digital media.


Data - Facts that are collected and stored in a database system.




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Determining characteristic of unstructured data - It does not follow a data model.


Flat files - They contain no internal hierarchical organization.


Data retrieval before database management systems - Sequentially from simple files.


Primary Key - An attribute or group of attributes that uniquely identify a tuple in a
relation.


Foreign Key matching - 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 - What uniquely identifies each entity in a collection of entities but is not
the primary key.


Candidate Key - A set of columns in a table that can uniquely identify any record in that
table without referring to other data.


Database indexing - The original data is copied to the index.


Indexes in physical database design - To retrieve data DIRECTLY using a pointer.


Index creation on a database column - To optimize data retrievals.


Functional Dependency - Each value of a column relates to at MOST one value of
another column.



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Rules/Appearance of First Normal Form - - 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 - - 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 - - All non-key columns depend ONLY on the
primary key - Tables are totally free of data redundancy.


Differences between operational and analytical databases - - Volatility - Detail - Scope -
History.


Volatility - Database updates in real time. Operational Data is Volatile. Analytical Data is
NOT Volatile.


Detail in databases - - A database that keeps record of individual transactions; line items -
Operational: Detailed - Analytical: Detailed.


Scope in databases - - How far a database can reach - Operational: incompatible -
Analytical: Enterprise-Wide/Summary.


History in databases - - Whether DB is current or tracks all data - Operational: Current
only - Analytical: Tracks trends.


Data warehouse refresh process - 1. Extraction 2. Cleanse 3. Integrate 4. Restructure 5.
Load.




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Extraction in ETL - Data extracted and put into staging area.


Cleanse in ETL - Errors are eliminated from data; standard abbreviations applied.


Integrate in ETL - Data is put into a uniform structure; Data converted to uniform
structure.


Restructure in ETL - Data is structured in a design that is optimal for analysis.


Load in ETL - Data is loaded to the data warehouse.


Issue focused on 'Load' component of ETL - Monitor refreshing volume and frequency.


Step in ETL Process where raw data is aggregated - Transformation steps.


Data mining activities - 1. Clustering & Segmentation 2. Classification 3. Estimation 4.
Prediction 5. Affinity Grouping 6. Description.


Clustering & Segmentation - Taking large entity and dividing into smaller groups of
entities. Useful when unsure of what looking for.


Classification (Data Mining) - Organizing data into predefined classes.


Estimation (Data Mining) - Assigning a numeric value to an object.


Prediction (Data Mining) - Classifying objects according to an expected future behavior.



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