For Data analysts
Build breakdowns and check comparisons.
Reduce repeated breakdown and comparison setup with Tables, supported Stats, a read-only data profile, and supplied Python on Max.
Upload your spreadsheet free
How it plays out
Inspect survey or feedback data, prepare a breakdown or comparison, and check assumptions before reporting.
Situation
Inspect survey or feedback data for missing or duplicate records before preparing a breakdown or comparison.
How to get there
- Upload the spreadsheet and select a worksheet; your automatic first Brief starts in the file chat.
- Review the first Brief alongside the read-only Data profile for columns, missing values, and health flags.
- Use Tables on Pro or Max or supported Stats on Max for the requested analysis; use Brief and Ask for context and follow-ups.
- Review figures, bases, and assumptions, including supplied Python on Max where available; check flags against the source and correct confirmed issues there.
What you get
- A read-only column profile with missing-value and duplicate-row flags.
- Descriptive breakdowns and supported comparisons on eligible plans.
- Findings with figures to review and supplied Python on Max where available.
Reduce repeated setup; give stakeholders figures and bases to check while keeping source corrections and judgment yours.
Illustrative example
Data quality checked in ~1 secRepresentative 48-row sample estimate, not a timed action in this preview. File size and task vary; loading and display affect total elapsed time; not a browser completion guarantee.
A colleague hands over an unfamiliar survey export. Before comparing group averages, you need to see where confidence scores are missing.
Upload the export and inspect its read-only data profile; ask: “Which group has the most missing confidence scores before I compare averages?”
A read-only data profile and an answer identifying where confidence scores are blank by group, so you can check the source before comparing averages.
Where each tool fits
Inspect the profile, then use Tables on Pro or Max or supported Stats on Max; Brief and Ask add context.
Why DataWhisperer?
Check the export before comparing scores.
An unfamiliar file deserves a look at its recorded values before averages become a readout.
Find the blanks that affect the comparison
Inspect missing confidence scores and duplicate rows in the read-only profile; check the source.
See which group loses score records
Ask where confidence ratings are blank by group to check nonblank bases.
Common questions
How can I get familiar with a new dataset?
Upload the file to start your first Brief automatically. Inspect the read-only data profile for missing values and duplicate rows alongside the readout.
Will this fix the flagged data?
The profile and health checks identify rows and columns for your review. Confirm issues against the source, make any corrections there, and upload the revised file.
Are the example numbers on this site from real customer data?
These are examples, not customer data.