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North Carolina Data Architecture Certification Exam Questions and Correct Answers | Complete Exam Preparation Guide

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Prepare for the North Carolina Data Architecture Certification Exam with this comprehensive collection of exam questions and correct answers. This exam preparation resource covers data architecture principles, conceptual and logical data modeling, database design, data integration, data governance, data quality, metadata management, master data management, data warehouses, data lakes, cloud data architecture, security, scalability, performance optimization, and enterprise data management. Ideal for data architects, database professionals, data engineers, business intelligence specialists, IT professionals, and certification candidates seeking to strengthen their data architecture knowledge and exam readiness.

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North Carolina Data Architecture Certification
Exam Question and correct answers (verified
answers 100%) Q&A 2026/2027 INSTANT
DOWNLOAD PDF

1. What is the primary goal of data architecture?
A. To replace database administrators
B. To define how data is collected, stored, integrated, and used across an
organization
C. To eliminate all data security risks
D. To create only physical databases
Correct Answer: B
Rationale: Data architecture provides a blueprint for managing organizational
data assets, including data storage, integration, governance, and usage patterns.


2. Which component defines how data moves between systems?
A. Data lineage
B. Data flow architecture
C. Data dictionary
D. Data modeling
Correct Answer: B
Rationale: Data flow architecture describes the movement and transformation of
data between applications, databases, and platforms.


3. A conceptual data model primarily focuses on:

,A. Database indexes
B. Physical storage structures
C. High-level business entities and relationships
D. SQL query optimization
Correct Answer: C
Rationale: A conceptual model represents business concepts such as customers,
products, and transactions without technical implementation details.


4. Which data model level includes tables, columns, and keys?
A. Conceptual model
B. Logical model
C. Physical model
D. Enterprise model
Correct Answer: C
Rationale: The physical data model describes actual database structures including
tables, fields, indexes, and constraints.


5. What is the purpose of a primary key?
A. To encrypt database records
B. To uniquely identify each record in a table
C. To create database backups
D. To improve network speed
Correct Answer: B
Rationale: A primary key ensures that every record in a table can be uniquely
identified.


6. Which architecture style stores data in a central repository for analysis?

,A. Data warehouse architecture
B. Peer-to-peer architecture
C. Distributed file architecture
D. Presentation architecture
Correct Answer: A
Rationale: Data warehouse architecture consolidates historical data from multiple
sources for reporting and analytics.


7. What does ETL stand for?
A. Extract, Transfer, Load
B. Extract, Transform, Load
C. Evaluate, Test, Link
D. Encode, Translate, Load
Correct Answer: B
Rationale: ETL processes extract data from sources, transform it into usable
formats, and load it into target systems.


8. Which principle ensures that data remains accurate and reliable?
A. Data quality management
B. Data duplication
C. Data isolation
D. Data compression
Correct Answer: A
Rationale: Data quality management establishes processes to maintain accuracy,
completeness, consistency, and reliability.


9. What is the main purpose of a data dictionary?

, A. To store passwords
B. To document data elements and their meanings
C. To replace databases
D. To create network connections
Correct Answer: B
Rationale: A data dictionary provides metadata describing data elements,
definitions, formats, and relationships.


10. Which architecture supports real-time data processing?
A. Batch-only architecture
B. Streaming data architecture
C. Static file architecture
D. Manual reporting architecture
Correct Answer: B
Rationale: Streaming architectures process data continuously as it is generated,
enabling real-time analytics.


11. What does normalization reduce in relational databases?
A. Data security
B. Data redundancy
C. Data availability
D. Query capability
Correct Answer: B
Rationale: Normalization organizes data structures to minimize duplication and
improve consistency.


12. Which database type is best suited for highly structured transactional data?

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