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Issue: Sometimes individual queries to a Saas server will fail or time-out, which results in storing incomplete data into its the intermediate database (i.e. missing data for some machines). Also on rare occasions, a server may be temporarily unavailable which can cause an entire server to be skipped. This partial data is ‘staged’ for an upcoming cube build. Later, when the cube builds, it will build using this partial data. This partial data will then be visible to users in their Analytics dashboards.
Impact: Primarily This primarily impacts the live-data window (within 45 to 60 days), for random groups of machines and servers. This missing data is temporary until the next build cycle.
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When a build is skipped due to detected partial data, it means that the previous cube build will remain as the source for analytics dashboards. For example, let’s say assume cubes build every 30 minutes, and the last successful build was at 10:00 AM. If a the 10:30 build cycle has partial data detected, it will be skipped, and the existing 10:00 AM cube build will remain in place until it is later replaced by the next build cycle at 11:00AM.
Although unlikely, if more than one partial build occurs in a row, the ‘skipping’ ‘build skipping’ will continue, and the period between cube builds will be longer than the typical expected cycleextend for a longer period until a successful build is created.
Appendix: Analytics Architecture Overview
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