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.
Contact Information
Full Name
*
First Name
Last Name
Email
*
example@example.com
Company
*
Phone Number
*
Please enter a valid phone number.
Format: (000) 000-0000.
Context
Department
*
Please Select
Finance
Operations
Sales
Marketing
IT
Human Resources
Customer Support
Data/Analytics
Legal
Other
Role
*
Please Select
Data custodian (Data scientist, system managers)
Data consumer (Use data for analysis & decisions)
Data collector (Business intelligence)
Primary Data Worked With
*
Please Select
Customer Data
Financial Data
Operational Data
Product Data
Employee Data
Sales Data
Support Data
Master Data
Other
Pain points and business impact
How often do you experience data quality issues?
*
Never
Rarely
Sometimes
Often
Very often
What is the biggest impact of poor data quality? (Select up to 2)
*
Delays in work
Incorrect decisions
Extra rework
Customer dissatisfaction
Reporting errors
Compliance risk
Other
How many hours per week do you spend dealing with bad data?
*
What systems do you use?
Data Quality Assessment
Core Data Quality
*
Rows
1
2
3
4
5
6
7
8
9
10
Data is accurate
Data is complete (not missing key fields)
Data is consistent across systems
Data is up-to-date
Data is easy to access
Data is easy to understand
There is clear ownership of data
Overall, how severe is the impact of poor data quality?
Root Causes and Issue Handling
What are your main cause of data quality issues?
Manual data entry erros
Missing required fields / poor form design
Lack of validation rules
Duplicate records
Data not syncing between systems
Too many systems
Lack of ownership / accountabity
Poor data definitions / confusion
Outdated processes
Lack of monitoring / alerts
Other
Where issues most often originate?
Data entry (frontline input)
System integrations
Data transformations / pipelines
Reporting
Other
Ease of identifying root cause?
Worst
1
2
3
4
5
6
7
8
9
Best
10
1 is Worst, 10 is Best
Ease of fixing issues once identified?
Worst
1
2
3
4
5
6
7
8
9
Best
10
1 is Worst, 10 is Best
System Complexity
How many systems contain the data you need?
*
How is data moved between systems?
Scheduled jobs
API integration
External integrations
Manual (CSV / spreadsheets)
Other
How is data moved between people?
Email
Spreadsheet sharing
Chat/messaging
Scheduled jobs
Verbal handoff
Other
Process and Controls
Is data validated at entry?
*
Always
Usually
Sometimes
Rarely
Never
Are data issues detected quickly?
*
Always
Usually
Sometimes
Rarely
Never
Is there a clear process to fix data issues?
*
Yes
Partly
No
Not sure
Is data quality actively monitored?
*
Yes
Partly
No
Not sure
Are system user roles and responsibilities clearly defined?
*
Yes
Partly
No
Not sure
AI Readiness and Trust
Is the data clean enough to support AI and automation?
*
Yes
No
Not sure
How much do you trust reports and outputs generated from your data?
*
Do not trust
1
2
3
4
5
6
7
8
9
Fully trust
10
1 is Do not trust, 10 is Fully trust
Where could automation or AI help most?
Data cleanup
Error detection
Report generation
Data entry support
Workflow routing
Trend analysis
Other
Data Budget
How much do you currently invest in data quality each year?
Which budget range best describes your annual spend on data analysis?
Under $10,000
$10,000-$50,000
$50,000-$100,000
Over $100,000
How important is increasing the data quality budget next year?
1
2
3
4
Best
5
1 is , 5 is Best
What would you want to improve if you had a larger data quality and analysis budget?
Open Feedback
What is the most frustrating data issue you deal with?
Describe a recent example where bad data caused a problem.
What do you believe was the root cause of that issue?
If you could fix one thing about the data, what would it be?
Submit
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