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WGU C175 QUESTIONS AND ANSWERS 2025 UPDATED

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WGU C175 QUESTIONS AND ANSWERS 2025 UPDATED

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WGU C175/D426 DATA MANAGEMENT
FOUNDATIONS OA EXAM ACTUAL EXAM 2 LATEST
VERSIONS QUESTIONS AND CORRECT DETAILED
ANSWERS WITH RATIONALES

Modality - 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.

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

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.

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

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

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

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.

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.

, 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.

Referential integrity rules by modern relational database management systems - ANS-
Insert, Update, Delete.

DISTINCT clause - ANS-Returns only unique or 'distinct' values; Filters Data Results.

ORDER BY clause - ANS-Modifies presentation of data results.

Heap file - ANS-A file where records can be placed anywhere in the memory.

Hash file - ANS-A file that uses Hash function computation on some fields of the
records, and the result of that computation determines where the record is stored.

Major Joins - ANS-- LEFT JOIN - RIGHT JOIN - INNER JOIN - FULL JOIN.
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