Data Warehouse Administration — Focus Areas A data warehouse administrator is primarily concerned with which combination of responsibilities?

Introduction / Context:
Data warehouses support analytics and decision-making. Their administration blends classic DBA duties with performance and usability goals tailored to decision latency, workload management, and data availability for BI users.

Given Data / Assumptions:

• Data warehouse workloads are read-heavy, analytical, and periodic (ETL windows).
• Decision latency (time to insight) matters to stakeholders.
• DBA responsibilities (backup, security, capacity, performance) still apply.

Concept / Approach:
Whereas OLTP DBAs emphasize transaction throughput and minimal write latency, DW administrators emphasize fast query performance, partitioning, compression, workload isolation, and data freshness for reporting. Nonetheless, they do not abandon core DBA tasks such as security, backup/recovery, and monitoring. Therefore, combining “time to make a decision” with “typical DBA roles” best captures their remit.

Step-by-Step Solution:
Identify analytics-oriented KPI: decision time (query performance, freshness).Include classic DBA duties: availability, security, backup/recovery, indexing/partitioning.Exclude broad application redesign as primary DW admin scope.Select the combined focus in option B.

Verification / Alternative check:
Common DW frameworks (Kimball/Inmon) still assume DBA practices while adding MPP tuning, columnar storage, and ETL SLAs to meet analytical timelines.

Why Other Options Are Wrong:

• A: Ignores necessary DBA responsibilities.
• C/D: Application redesign is typically an application or data engineering function, not core DW admin.
• E: ETL is part of the pipeline, but operations and administration remain essential.

Common Pitfalls:
Over-focusing on ETL while neglecting governance, security, and recoverability in the warehouse.

Final Answer:
The time to make a decision and the typical roles of a database administrator