You are required to report on hourly average response time of the last 60 days. How should you configure your data collection and summarization parameters to meet these requirements without unnecessarily using database size?

You are required to report on hourly average response time of the last 60 days. How should you configure your data collection and summarization parameters to meet these requirements without unnecessarily using database size?

• A. Summarize detailed data into hourly data after 30 days, summarize hourly data into daily data after 60 days
• B. Keep all detailed data for 60 days
• C. Summarize daily data into hourly data after 60 days
• D. Do not summarize; export to external database

Answer: (A)

Tiered data retention with aging is the idea here: you balance granularity and storage by progressively aggregating data as it ages. To report hourly average response time for the last 60 days, keep the detailed, granular data for a short window (30 days) so you have high-fidelity near-term information. Once data moves beyond that window, summarize it to hourly granularity, ensuring the entire 60-day period is available in hourly form. After data passes 60 days, further reduce storage by summarizing the hourly data into daily averages for older records. This preserves the required hourly resolution for the most recent 60 days while keeping storage manageable. Keeping all detailed data for 60 days would waste space. Summarizing daily data into hourly data after 60 days isn’t feasible because you can’t recover hourly detail from daily summaries. Exporting raw data externally avoids in-system summarization and can complicate reporting and maintenance. The chosen approach provides the needed hourly view for the 60-day window with sensible long-term storage reductions.

Tiered data retention with aging is the idea here: you balance granularity and storage by progressively aggregating data as it ages. To report hourly average response time for the last 60 days, keep the detailed, granular data for a short window (30 days) so you have high-fidelity near-term information. Once data moves beyond that window, summarize it to hourly granularity, ensuring the entire 60-day period is available in hourly form. After data passes 60 days, further reduce storage by summarizing the hourly data into daily averages for older records. This preserves the required hourly resolution for the most recent 60 days while keeping storage manageable.

Keeping all detailed data for 60 days would waste space. Summarizing daily data into hourly data after 60 days isn’t feasible because you can’t recover hourly detail from daily summaries. Exporting raw data externally avoids in-system summarization and can complicate reporting and maintenance. The chosen approach provides the needed hourly view for the 60-day window with sensible long-term storage reductions.