PHPMem v2.0.1
Version
1.6.45
Uptime
17 days 12 hours 12 minutes 28 seconds
Memory
Total
512MB
Used
12,72MB (2.48%)
Free
499,28MB
Keys
Current
14 060
Total (since start)
40 994
Evictions
0
Reclaimed
760
Expired Unfetched
0
Evicted Unfetched
0
Connections
Current
16 / 1 024 max
Total
238 576
Rejected
0
llm:bd12ef71844e93ed7d7854116cd61c0c3c3494d572aa76f7c03b8c7e90577f70
Edit
### 3.1 Quality Grade
The dataset earns an **A (Excellent), 100%**. Every field in `bedtime_screentime_sleep_debt` (8,500 rows) is fully populated, so analyses will not need to work around gaps or fill in missing values. Because this is a single table, referential integrity (100%) is structurally not applicable, so the grade rests mainly on completeness. Uniqueness could not be scored (N/A), so we cannot yet confirm that no records are duplicated.
### 3.2 Key Risk Areas
| Risk Type | Detail | Severity |
|-----------|--------|----------|
| PII/Sensitive | bedtime_screentime_sleep_debt.bedtime_phone_minutes (phone) | High |
This flag appears to come from the word "phone" in the column name. The name suggests a measure of nightly phone use in minutes, not a phone number, so it is likely a false positive. The evidence does not show the column's contents, so someone should confirm this before the data is shared or used for reporting or ML. It is the only risk identified, and confirming it is a quick check, not a structural problem.
### 3.3 Remediation Priorities
- **Confirm the sensitivity flag on `bedtime_phone_minutes`.** Have a data owner check that the column holds only numeric usage durations and no contact details. Then record the flag as a false positive so it does not recur.
- **Establish a uniqueness check on `bedtime_screentime_sleep_debt`.** Uniqueness is currently N/A. Designate a column, or a combination of columns, that identifies each record, then confirm that none of the 8,500 rows are duplicated.
- **Check that values are plausible, not just present.** Full completeness does not guarantee accuracy. Review the minutes and sleep-related measures for impossible values, such as negative durations or nightly totals beyond 24 hours, before the data feeds dashboards or models.
- **Plan for enrichment as the data grows.** If more data is added later, such as other periods or participant attributes, keep column definitions and units consistent with this table. Define any new tables with clear identifiers from the start, so the A grade carries over.