After reviewing observability data, you find that Tableau Server’s data extract refreshes are significantly impacting performance during business hours. What architectural change should be made to address this issue?
A.
Moving all data extracts to live connections to avoid refreshes
B.
Scheduling extract refreshes during off-peak hours to minimize impact on performance
C.
Completely disabling extract refreshes to enhance server performance
D.
Upgrading the server's CPU to speed up extract refreshes
Scheduling extract refreshes during off-peak hours to minimize impact on performance An effective architectural adjustment in response to performance impacts from data ex-tract refreshes is to reschedule these refreshes to off-peak hours. This change minimizes the performance impact during business hours when server demand is typically higher, thereby maintaining better overall server performance. Option A is incorrect because switching all data extracts to live connections might not be feasible or desirable for all data sources and can have its own performance implications. Option C is incorrect as completely disabling extract refreshes could compromise data freshness and functionality for users. Option D is incorrect because while upgrading the CPU may improve performance, it does not address the core issue of extract refreshes impacting server use during peak times.
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