Q01
Long Text
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Data Asset Discoverability, Documentation & Trust Survey
Measures how easily analytics teams can find, evaluate, and trust data assets across the organization, revealing gaps in metadata, documentation, and lineage practices. Designed for data and analytics professionals; estimated 6–8 minutes.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
25 questions · ~4 min
Q02
Multiple Choice
In the past 30 days, have you accessed or evaluated any data assets (e.g., tables, dashboards, or reports)?
Q03
Long Text
How would you rate your proficiency with your organization's data tools?
Q04
Long Text
Overall, how easy or difficult was it to find a suitable data asset in the past 30 days?
Q05
Multiple Choice
How did you discover the most recent data asset you used? Select all that apply.
Q06
Multiple Choice
For the last data asset you used, was documentation available?
Q07
Long Text
How confident are you in the accuracy and reliability of the last data asset you used?
Q08
Long Text
Rank the following areas by how much they would improve your data experience. Drag to reorder from most to least impactful.
Q09
Long Text
Based on your responses, is there anything else you'd like to share about finding, documenting, or trusting data assets in your organization?
Q10
Multiple Choice
What is your primary role?
Q11
Long Text
Thank you for your time — your feedback will directly help us improve data discoverability, documentation, and trust across the organization.
Q12
Multiple Choice
In the past 30 days, what challenges, if any, did you encounter when trying to use data assets? Select all that apply.
Q13
Long Text
When you search in your organization's data catalog or portal, how often do the first-page results meet your needs?
Q14
Long Text
How would you rate the completeness of the documentation for that data asset?
Q15
Long Text
Rank the following factors by how much they influence your confidence in a data asset. Drag to reorder from most to least important.
Q16
AI Interview
We'd like to understand your experience in more depth. An AI moderator will ask you a couple of follow-up questions about your data discovery and trust experience.
Q17
Multiple Choice
Which domain or team do you primarily support?
Q18
Long Text
How would you rate the clarity of the documentation for that data asset?
Q19
Long Text
How likely are you to reuse this data asset for future analyses?
Q20
Long Text
How long have you been at your current organization?
Q21
Long Text
How would you rate the recency (up-to-dateness) of the documentation for that data asset?
Q22
Long Text
How likely are you to recommend this data asset to a colleague?
Q23
Long Text
Where are you primarily located?
Q24
Long Text
How would you rate the lineage and provenance information in the documentation for that data asset?
Q25
Long Text
What is the maximum acceptable data freshness (latency) for your typical analyses?
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.