Internal Data Product SLA Expectations Survey

Thank you for participating in this survey about our internal data products. We're gathering your expectations around reliability (uptime), data freshness, and data quality to set clear, realistic service-level targets. This survey takes approximately 9 minutes. Your participation is voluntary and you may stop at any time. Responses will be anonymized and reported in aggregate to the data platform team. There are no right or wrong answers—we simply want your honest expectations.

How often do you use internal data products (dashboards, datasets, pipelines) in your work?

• Daily
• 2–3 times per week
• Weekly
• Less than weekly
• Rarely or never

What minimum monthly availability (uptime) do you expect from the data products you rely on?

• 99.0% (~7.3 hours downtime/month)
• 99.5% (~3.6 hours downtime/month)
• 99.9% (~43 minutes downtime/month)
• 99.95% (~22 minutes downtime/month)
• Unsure

What is the minimum acceptable overall data accuracy rate for your production use?

• 99.9% or higher
• 99.5%
• 99.0%
• 97%
• 95%
• 90%
• Below 90%
• Unsure

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

Based on your responses, is there anything else we should consider about your data reliability, freshness, or quality expectations? Please share any additional context, pain points, or priorities.

What is your primary role?

• Data analyst
• Data engineer
• Data scientist
• Product manager
• Software engineer
• Business stakeholder
• Other (please specify)

Thank you for your input. Your responses will help us define clear, realistic service-level targets for our internal data products. We expect to share proposed SLOs with stakeholders within the coming weeks.

How critical are internal data products for completing your work on time?

Which planned maintenance windows are acceptable to you? 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 is the maximum acceptable duplicate record rate in datasets delivered to you?

• 0% (no duplicates tolerated)
• Under 0.1%
• Under 0.5%
• Under 1%
• Under 2%
• Under 5%
• Unsure

What are your preferred channels for incident and maintenance notifications? Select all that apply.

• Slack/Teams
• Email
• Status page
• PagerDuty/On-call
• In-product banner
• Other (please specify)

Which team or department are you part of?

• Analytics
• Data platform
• Finance
• Operations
• Marketing
• Sales
• Product
• Engineering
• Other

What data freshness (maximum acceptable lag) do you require for your primary workflows?

• Real-time (under 1 minute)
• Under 15 minutes
• Under 1 hour
• Under 6 hours
• Under 24 hours
• Weekly or less frequently
• Unsure

Please rank the following data quality dimensions by importance to your work (drag to reorder, 1 = most important).

1. Accuracy
2. Completeness
3. Timeliness
4. Consistency
5. Validity
6. Lineage/transparency

How many years of experience do you have working with data in your current or similar roles?

• Under 1 year
• 1–2 years
• 3–5 years
• 6–10 years
• More than 10 years

What is your primary working time zone?

• UTC−8 to −5 (Americas)
• UTC−4 to 0 (Atlantic/Europe West)
• UTC+1 to +3 (Europe/Africa)
• UTC+4 to +7 (Middle East/Asia)
• UTC+8 to +10 (East Asia/Australia)
• UTC+11 to +12 (Pacific)
• Prefer not to say