SAP Certified - Database Administrator - SAP HANA : C_DBADM_2601

A regional event management company runs SAP HANA for ticket sales analytics. SAP HANA cockpit shows the database as available, but the operations team observes that statement-level troubleshooting evidence is missing for one reporting window. The general performance dashboard shows a brief response-time increase, while the detailed statement history has no entries for the affected period. A support coordinator proposes adjusting report schedules because the dashboard indicates a slowdown.
The constraint is that the administrator must validate the diagnostic evidence path before changing workload timing. The next reporting window must remain available while the team confirms why detailed statement evidence was not captured.
Which action best addresses the troubleshooting gap?

• A. Ignore the issue because the database remained available and only detailed troubleshooting evidence was missing.
• B. Verify the statement-history collection path for the affected period, correct the collection issue, and validate captured evidence in the next window.
• C. Change the report schedule immediately because the response-time increase proves the workload timing is wrong.
• D. Restart SAP HANA before the next window so the detailed statement history starts with a clean monitoring state.

A digital publishing company operates SAP HANA for subscriber activity reporting. Users report that dashboards are available, but refresh times vary sharply during the morning reporting window. SAP HANA cockpit shows no service outage, while monitoring history shows a recurring peak in expensive statement activity from a reporting workload. The database team is asked to increase system capacity immediately because the reports are business-critical.
The constraint is that the administrator must identify the execution pattern before recommending a capacity or scheduling change. The business requires stable refresh times, but the system must remain available during investigation.
Which action best fits the observed performance evidence?

• A. Review the expensive statement pattern and workload timing, then apply a targeted scheduling or workload adjustment based on validated evidence.
• B. Restart SAP HANA during the reporting window so existing expensive statements are cleared before users refresh dashboards.
• C. Disable the reporting workload until the next maintenance window so all expensive statements are removed from the system.
• D. Increase capacity immediately because dashboard variability always indicates insufficient database resources.

A regional print services company is rehearsing a phased migration from SAP HANA on-premises to SAP HANA Cloud. The export completes, the target database is reachable, and database explorer confirms that sample queries return dat a. During review, the administrator finds that the rehearsal workbook does not include a comparison of administration checks between the source system before export and the cloud target after import. The project lead wants approval because the query results are correct.
The constraint is that the migration wave must prove operational transition readiness, not only data access. The validation pattern must show that source administration evidence and target administration evidence were captured at the correct points in the migration sequence.
Which recommendation is most appropriate?

• A. Capture source pre-export administration evidence and target post-import administration evidence, then approve only after both are validated.
• B. Approve the rehearsal because successful target queries prove that the migrated data is usable.
• C. Repeat the source export because missing administration comparison means the data movement failed.
• D. Defer administration comparison until production cutover so the rehearsal can focus only on transfer completion.

A manufacturing firm uses SAP HANA Cloud for analytics and an on-premises SAP HANA system for operational reporting. After a weekend parameter change, users report that a recurring operational report now completes, but much more slowly than before. Monitoring shows the database is available, CPU is elevated during the report window, and memory consumption remains within expected limits. A junior administrator proposes increasing system resources immediately.
The team lead wants the least disruptive action first because the slowdown affects only one workload pattern, not the entire database. The administrators can review runtime indicators and configuration settings through the available administration tools.
Which action is the best first step?

• A. Increase database resources first because the higher CPU usage proves the current sizing is no longer sufficient.
• B. Compare the changed configuration with current workload behavior and validate whether the parameter shift altered execution characteristics for that report pattern.
• C. Roll back the recent parameter change immediately without validating whether it is linked to the report slowdown.
• D. Restart the affected database so that the report executes with a clean runtime state and lower CPU utilization.

A regional insurance claims processor runs SAP HANA for daily operational reporting. After a scheduled workload increase, SAP HANA cockpit shows higher memory usage and slower report response times. The alert list shows a threshold warning, but the operations note only records that reports are "slow." A support analyst proposes increasing the threshold so the warning no longer appears.
The constraint is that the administrator must determine whether the warning represents a real workload pattern requiring follow-up or only an alert configuration mismatch. The response must preserve monitoring usefulness for future workload changes.
Which action best addresses the monitoring issue?

• A. Increase the alert threshold immediately because users already reported slow response times.
• B. Disable the alert temporarily so operational reports can continue without monitoring noise.
• C. Correlate the alert timing with workload and memory behavior, update the monitoring evidence, and adjust thresholds only if the observed baseline supports it.
• D. Restart the database so memory usage returns to normal before the next reporting cycle.