We’re aligning on expected reliability (uptime), data freshness, and data quality thresholds for key internal data products.
How often do you use these data products for your work?
How critical are these data products for completing your work on time?
What minimum monthly availability (uptime) do you expect?
- 99.0%
- 99.5%
- 99.9%
- 99.95%
- Unsure
Which planned maintenance windows are acceptable? Select all that apply.
- No regular windows acceptable
- Weeknights 6–10 pm (local)
- Overnight 10 pm–6 am (local)
- Weekends
- Flexible with advance notice
What data freshness do you require for your primary workflows?
- Real-time (<1 minute)
- Under 15 minutes
- Under 1 hour
- Under 6 hours
- Under 24 hours
- Weekly or less frequently
- Unsure
Minimum acceptable overall data accuracy (%) for production use. Enter a whole number between 0 and 100.
Maximum acceptable duplicate record rate (%) in delivered datasets. Enter a whole number between 0 and 100.
Rank these quality dimensions by importance to you (1 = most important).
How quickly should we notify you when a data incident is detected?
- Immediately
- Within 15 minutes
- Within 1 hour
- Within 4 hours
- Same business day
- Next business day
Preferred channels for incident and maintenance notifications (select all that apply):
- Slack/Teams
- Email
- Status page
- PagerDuty/On-call
- In-product banner
What is your primary role?
- Data analyst
- Data engineer
- Data scientist
- Product manager
- Software engineer
- Business stakeholder
- Other/Prefer to self-describe
Which team or department are you part of?
Years of experience working with data in your role
Attention check: To confirm you are reading carefully, please select “I am paying attention.”
- I am paying attention
- I am not paying attention
- Please skip this question
Anything else we should consider about availability, freshness, or quality guarantees?
Max 600 chars
AI Interview: 2 Follow-up Questions on availability, freshness, and quality expectations
Thanks for your time—your input will help us set clear and realistic reliability and data freshness targets.