What is the purpose of data modeling languages?
Short answer
A to describe a data schema convertible into any data encoding format
Question
Key Takeaways
The exam tests your understanding that data modeling languages describe data schemas convertible into multiple encoding formats, not binary decoding or CPU translation.
Data modeling languages like YANG define structured schemas for network device configuration and operational data, enabling interoperability across vendors. The community consensus strongly supports option A, highlighting their role in generating code or data representations in formats like XML and JSON.
Common mistake: Some candidates mistakenly choose option C, confusing data modeling languages with protocol decoding or binary parsing mechanisms.
Expert Analysis
Why the Answer Is Correct
Option A correctly states that data modeling languages describe a data schema convertible into any data encoding format. YANG, for example, defines the structure, relationships, and constraints of data elements, which can then be encoded into XML, JSON, or other formats. This aligns with the purpose of model-driven programmability in modern networks.
Why the Other Options Are Wrong
Option B describes data flow patterns, which is more related to network monitoring or telemetry, not data modeling. Option C refers to decoding binary-encoded PDUs, which is the role of protocol specifications, not data modeling languages. Option D discusses CPU architecture interoperability, which is unrelated to data modeling and more relevant to binary instruction sets or ABI standards.
Community Comment Notes
Comment 1 accurately summarizes that data modeling languages define structure, relationships, and constraints, enabling generation of code or data in various formats. Comment 2 adds valuable context by noting that these models define network device configuration, simplify automation, and work across vendors. Comments 3 and 4 confirm the consensus that A is the correct answer.
Official Reference
https://datatracker.ietf.org/doc/html/rfc7950
This link opens the official vendor documentation in a new tab.
Exam Strategy
When encountering questions about data modeling languages, focus on keywords like 'schema,' 'structure,' and 'encoding formats.' Eliminate options that mention binary decoding, CPU architectures, or data flow patterns, as these are unrelated to the core purpose of data modeling.
Community Votes
100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.
Discussion 4 contributions
Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.
From public community threads 4
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[Removed] 👍 2A is correct GPT 4: This statement is accurate. Data modeling languages allow you to define the structure, relationships, and constraints of data elements. These models can then be used to generate code or data representations in various formats, such as XML, JSON, or database schemas.
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chiacche 👍 11. Provides a structured, standardized way to define data structure, format, semantics, and relationships. 2. Defines network device configuration models 3. Simplifies the development of automation scripts and tools. 4. Works across different vendors’ devices.
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slacker_at_work 👍 2 Answered AThis must be A
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Luiggi 👍 2 Answered Acorrect answer
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