Data Completeness Check — 技能工具
v1.0.0数据完整性判断机制。通过前晚基准值 vs 早上值对比,判断 Power BI 数据是否回灌完毕。适用于任何有延迟回灌的数据源。避免发送不完整数据。
详细分析 ▾
运行时依赖
版本
- Introduced a data completeness checking mechanism based on dual time-point comparison (late night vs. morning values). - Outlined decision rules to verify if Power BI data has been fully updated before sending reports, preventing incomplete data delivery. - Provided practical reference thresholds for key metrics (e.g., Paid Subs, Revenue) on weekdays and weekends/holidays. - Made the approach generalizable for any delayed (T+1) data sources by selecting a key "sentinel" metric and establishing experience-based reference ranges.
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技能文档
Overview
This skill provides a mechanism to check data completeness before sending reports. It compares a "sentinel" metric captured at two time points (late night vs. morning) to determine whether the data has been fully backfilled.
When to Use
- Before sending Power BI reports or dashboards
- When data sources have known T+1 delay (data available next day)
- To prevent sending incomplete or stale data to stakeholders
How It Works
1. Select a Sentinel Metric
Choose a key metric that:
- Is reliably updated when data refresh completes
- Has predictable values (e.g., Paid Subscriptions, Total Revenue)
- Serves as an indicator that the full data pipeline has finished
2. Capture Values at Two Time Points
| Time Point | Typical Value | Purpose |
|---|---|---|
| 23:30 (previous night) | Baseline/previous day final value | Reference point |
| 09:00 (morning) | Current day partial or complete value | Check if refresh completed |
3. Compare and Decide
IF morning_value >= threshold_percentage of baseline_value:
THEN data is complete -> proceed to send report
ELSE data may be incomplete -> wait and retry or alert
Reference Thresholds
Weekdays (Monday - Friday)
- Paid Subs: Expect 95-105% of previous day
- Revenue: Expect 90-110% of previous day (depends on time of month)
- Active Users: Expect 85-100% of previous day
Weekends/Holidays
- Paid Subs: Expect 100-110% (may include weekend signups)
- Revenue: Expect 80-120% (higher variance)
- Active Users: Expect 60-90% (lower weekend activity)
Retry Logic
If data appears incomplete:
- Wait 30 minutes
- Re-capture the sentinel metric
- Compare again against threshold
- If still incomplete after 3 attempts, alert or skip sending
Generalization to Other Data Sources
This approach can be adapted for any T+1 data source:
- Identify a suitable sentinel metric
- Establish baseline reference ranges based on historical data
- Define threshold percentages for "complete" vs "incomplete"
- Implement the two-timepoint comparison workflow
Example Prompt
Check if the Power BI data is ready for today's sales report. Capture the total subscription count at 23:30 yesterday and 09:00 today. If the morning value is at least 95% of the previous night value, consider the data complete and send the report. Otherwise, wait 30 minutes and retry up to 3 times.
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