Data Lineage Trust & Impact Analysis Survey
Measures data practitioners' confidence in lineage accuracy, impact analysis efficiency, and tooling gaps. Designed for data engineering, analytics, and platform teams to identify high-priority improvements to lineage infrastructure and workflows.
設問の例
テンプレートの内容をプレビューできます。すべての設問は公開前に自由に編集できます。
In the last 30 days, how often did you use data lineage or impact analysis tools?
- Daily
- Several times a week
- Weekly
- Every few weeks
- Monthly or less
- I did not use them in the last 30 days
Overall, how much do you trust the accuracy of data lineage for your work over the last 30 days?
How would you rate the speed of completing a typical impact analysis over the last 30 days?
What are the biggest blockers to trustworthy lineage and efficient impact analysis for you? Select all that apply.
- Incomplete coverage
- Stale or delayed updates
- Unclear ownership or contacts
- Low metadata quality
- Tool usability or learnability
- Missing column-level lineage
- Access or permissions issues
- Query parsing limitations
- Competing priorities or time constraints
- Other (please specify)
Rank the following outcomes by importance for your work (drag to reorder; 1 = most important).
- Accurate coverage
- Faster impact scoping
- Fewer false positives
- Ease of use
- Clear ownership links
- Proactive change alerts
What is your primary role?
- Data engineer
- Analytics engineer
- Data analyst / BI developer
- Data scientist / ML practitioner
- Data platform / Infrastructure
- Product manager
- People manager / Leader
- Other
Thank you for completing this survey. Your feedback will directly inform improvements to lineage tooling and workflows. If you have any questions, please contact [survey administrator email].
Which systems did you use for data lineage or impact analysis in the last 30 days? Select all that apply.
- Data catalog (e.g., DataHub, Collibra, Alation)
- dbt docs
- OpenLineage-based tooling
- In-house lineage service
- BI lineage (e.g., Looker, Power BI, Tableau)
- Graph database or store
- Custom SQL or notebooks
- Other (please specify)
How confident are you in the accuracy of column-level lineage information you have access to?
Which best describes the focus of your most recent impact analysis in the last 30 days?
- Upstream schema change
- Downstream dashboard or report change
- Production incident or root-cause analysis
- Cost or performance optimization
- Access or governance change
- Other (please specify)
Which methods do you use to validate or cross-check lineage information when making decisions? Select all that apply.
- Compare with query logs
- Manual SQL tracing
- Ask a subject matter expert
- Review dbt tests or data tests
- Graph traversal checks
- Cross-environment diffs
- Other (please specify)
- I don't validate lineage
If you could change one thing to improve lineage trust or impact analysis at your organization, what would it be?
How many years have you worked with data professionally?
- Less than 1 year
- 1–2 years
- 3–5 years
- 6–10 years
- 11+ years
- Prefer not to say
How confident are you in lineage coverage across different systems and platforms in your organization?
For your most recent impact analysis, how confident were you that you identified all affected assets?
What lineage update freshness do you typically need to trust lineage data for impact analysis?
- Real-time (under 5 minutes)
- Hourly
- Daily
- Weekly
- No strict requirement
Briefly describe a recent case (within the last 30 days) where lineage information either helped or misled your analysis. What happened, and how was it resolved?
Approximately how large is your organization?
- 1–49
- 50–249
- 250–999
- 1,000–4,999
- 5,000+
- Prefer not to say
How confident are you in the timeliness of lineage updates (i.e., that lineage reflects recent changes)?
On average, approximately how long did it take you to complete an impact analysis over the last 30 days?
- Under 15 minutes
- 15–30 minutes
- 31–60 minutes
- 1–2 hours
- More than 2 hours
- Not sure
Thank you for sharing your experiences. I'd like to explore a few of your answers in more depth. Based on what you've shared, could you walk me through a specific moment where lineage data influenced a decision you made — and what the outcome was?
Which industry best describes your organization?
- Technology
- Financial services
- Retail / CPG
- Healthcare / Life sciences
- Manufacturing
- Media / Entertainment
- Public sector / Education
- Other
- Prefer not to say
How confident are you in the accuracy of ownership and contact metadata associated with lineage?
Which region do you primarily work in?
- North America
- Europe
- Asia
- Latin America
- Middle East / Africa
- Oceania
- Prefer not to say
In the last 30 days, approximately how many times did lineage inaccuracies or gaps cause you to redo work?
- 0 times
- 1–2 times
- 3–5 times
- 6–10 times
- 11 or more times
- Not sure
含まれる機能
AIによる深掘り
自由回答に合わせてAIが追加で質問し、固定のフォームでは拾えない具体的な内容を引き出します。
注意確認設問
急いだ回答や質の低い回答者を除外する仕組みを標準で備えています。
AIが作成する設問文
文言、設問の順序、条件分岐をAIが調査の目的に合わせて作成します。
自動レポート
回答が集まると、テーマ、引用、わかりやすい要約が自動で作成されます。
他ツールとの比較
ほかのアンケートツールで最も近いテンプレートを調べました。それぞれの優れている点と、このテンプレートがさらに踏み込んでいる点をまとめています。
このテンプレートを選ぶ理由
- Combines opinion-scale confidence ratings across lineage accuracy, column-level lineage, cross-system coverage, timeliness, and ownership metadata for a granular trust profile
- Pairs quantitative impact-analysis speed and confidence metrics with open-text prompts asking practitioners to describe a specific recent lineage failure, grounding results in real incidents
- Includes an AI follow-up interview stage that can adaptively probe individual respondents' answers (e.g., digging into blockers or validation methods) rather than stopping at fixed-choice data
- Segments results by role, tenure, org size, industry, and region, and closes with a ranking exercise so priorities can be weighed against practitioner context
SurveySparrow
Business Impact Analysis Questionnaire Template | For IT, SaaSThis is a general-purpose IT/SaaS business impact analysis questionnaire rather than one built specifically for data lineage or impact-analysis tooling in data engineering workflows. It's a ready-to-field template but covers broad business continuity/impact concepts rather than lineage accuracy, column-level confidence, or tooling gaps. Useful as a generic starting point, but not purpose-built for data practitioners.
優れている点
- Ready-to-field template with SurveySparrow's conversational survey UI
- Applicable across general IT/SaaS business continuity and impact scenarios
- Likely supports standard question types (rating, multiple choice) for quick deployment
物足りない点
- No adaptive AI follow-up interviews or voice AI to probe individual responses in depth
- Not tailored to data lineage specifics (column-level lineage, ownership metadata, lineage freshness)
- No transparent published methodology or automated quality scoring per response
よくあるご質問
「Data Lineage Trust & Impact Analysis Survey」テンプレートにはどのような設問が含まれていますか?
すぐに使える設問が26問含まれており、最初の設問は次のとおりです:「Welcome to the Data Lineage Trust & Impact Analysis Survey. This survey explores your experience with data lineage tool…」・「In the last 30 days, how often did you use data lineage or impact analysis tools?」・「Overall, how much do you trust the accuracy of data lineage for your work over the last 30 days?」。すべての設問は上でプレビューでき、自由に編集できます。
このアンケートの回答にはどのくらい時間がかかりますか?
回答者は通常、26問を約11分で回答し終えます。
テンプレートは編集できますか?
はい。公開前であれば、すべての設問、選択肢、順序を編集できます。設問の追加や削除のほか、調査の目的に合わせた作り直しをAIエディターに依頼することもできます。
このテンプレートは無料で使えますか?
はい。エディターで開けば、すぐに編集を始められます。お試しにアカウントは不要で、無料プランでアンケートを公開できます。
公開の準備はできましたか?
このテンプレートをエディターで開いてみてください。最初の回答者が目にする前に、すべてを自由に変更できます。
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