Internal Data Quality Audit

Internal Data Quality Audit:

This should take 5-10 minutes to complete. Share your experience with data quality issues, root causes, systems complexity, controls, and readiness for AI/automation.
Context (Segmentation)
Your department?
Your role?
Primary data you work with?
Pain & Business Impact
How often do you experience data quality issues?
How much time do you spend dealing with bad data each week?
What is the biggest impact of poor data quality? (Select up to 2)
What systems do you use?
Core Data Quality (Score each question 1-10)
Overall, how severe is the impact of poor data quality?

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1 is Low impact, 10 is High impact
Data is accurate

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1 is Poor, 10 is Excellent
Data is complete (not missing key fields)

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1 is Poor, 10 is Excellent
Data is consistent across systems

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1 is Poor, 10 is Excellent
Data is up-to-date

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1 is Poor, 10 is Excellent
Data is easy to access

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1 is Poor, 10 is Excellent
Data is easy to understand

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1 is Poor, 10 is Excellent
There is clear ownership of data

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1 is Poor, 10 is Excellent
Root Cause Identification
Main causes of data quality issues

Other
Where issues most often originate
Ease of identifying the root cause

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1 is Very difficult, 10 is Very easy
Ease of fixing issues once identified

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1 is Very difficult, 10 is Very easy
Systems & Complexity
How many systems contain the data you need?
Are there discrepancies between systems?
How is data moved between systems?
How is data moved between people?
Process & Controls
Data is validated at entry

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1 is Strongly disagree, 10 is Strongly agree
Data issues are detected quickly

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1 is Strongly disagree, 10 is Strongly agree
There is a clear process to fix issues

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1 is Strongly disagree, 10 is Strongly agree
Data quality is actively monitored

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1 is Strongly disagree, 10 is Strongly agree
System user roles and responsibilities are clearly defined

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1 is Strongly disagree, 10 is Strongly agree
AI & Automation Readiness
Data is clean enough to support AI and automation

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1 is Not at all, 10 is Fully ready
You trust reports and outputs generated from this data

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1 is Do not trust, 10 is Fully trust
Where could automation or AI help most?
Open-Ended
What is the most frustrating data issue you deal with?
Describe a recent example where bad data caused a problem.
What do you believe is the root cause of that issue?
If you could fix one thing about your data, what would it be?
Should be Empty:

Internal Data Quality Audit:

Context (Segmentation)

Pain & Business Impact

Core Data Quality (Score each question 1-10)

Root Cause Identification

Systems & Complexity

Process & Controls

AI & Automation Readiness

Open-Ended