Components of a data warehouse Which of the following is NOT a component of a data warehouse architecture?

Introduction / Context:
A classic data warehouse ecosystem includes data ingestion and transformation tooling, the centralized analytical store, and rich metadata to document definitions, lineage, and usage. This question confirms that you recognize these standard parts and do not confuse them with OLTP application interfaces.

Given Data / Assumptions:

• We consider a conventional warehouse (on-prem or cloud) with ETL/ELT pipelines.
• Metadata is critical for governance and discoverability.
• The core warehouse tables hold integrated, historical, conformed data.

Concept / Approach:

Options A, B, and C all describe canonical warehouse components. “None of the above” is therefore correct in the sense that none are invalid. Note that OLTP transaction screens (not listed among A–D) are not warehouse components, but that choice is not an answer option; it simply illustrates the contrast between analytics and transactions.

Step-by-Step Solution:

Verification / Alternative check:

Industry references and vendor architectures (e.g., Kimball/Inmon patterns, modern cloud warehouses) include ingestion, storage, and metadata management as core pieces.

Why Other Options Are Wrong:

• Each of A–C is essential; rejecting any would break governance or pipelines.

Common Pitfalls:

• Confusing ELT vs ETL processing patterns; both are within the ingestion component.
• Ignoring metadata and lineage, which harms trust and reuse.

Final Answer:

None of the above; all are valid data warehouse components.