DatumFuse

AI Data Auditor

Diagnostics

AI Data Auditor

Get an instant health score for your dataset and uncover duplicates, missing values, and privacy risks before they impact decisions.

Audits Run

0total

Source Data

7 / 200 rows

Free (small dataset)

Ready to Audit

Paste data or upload a file to get your health score.

Need to validate millions of records?

DatumFuse Pro handles large-scale batch auditing through the API.

AI Data Diagnostics

Audit Your Data Health Before You Analyze

Bad data leads to bad decisions. Our AI Auditor performs a comprehensive health check on your dataset, grading it on completeness, uniqueness, and quality—so you know exactly what needs fixing.

Instant Data Grading

Get a simple A-F grade for your dataset. We analyze thousands of cells in seconds to give you a clear, objective quality score based on industry standards.

Issue Detection

We automatically flag critical issues like duplicates, missing values, inconsistent formatting, and invalid emails so you don't have to hunt for them manually.

Actionable Fixes

We don't just find problems; we tell you how to fix them. One-click recommendations link directly to our Cleaner, Anonymizer, or Enricher tools for immediate resolution.

Data Health Score

FScore: 42/100
243 Duplicate Records Found
Missing Values in 'Email' Column
Date Format Consistency Checked

Comprehensive Audit Checks

What we look for when we scan your files

Completeness

Identifies empty cells and null values across all columns to ensure dataset integrity.

Uniqueness

Detects exact duplicates and fuzzy matches to prevent redundant data processing.

PII Detection

Scans for sensitive info like emails, phone numbers, and SSNs that may need redaction.

Format Consistency

Checks if dates, phone numbers, and currencies follow a unified format.

Outlier Detection

Flags values that deviate significantly from the norm, indicating potential errors.

Validity Checks

Verifies if emails have valid domains and if numeric fields contain actual numbers.

Common Questions

Everything you need to know about the Data Auditor.

Contact Support
The score is a weighted average based on completeness (do you have missing data?), uniqueness (do you have duplicates?), and consistency. Critical issues like PII exposure or invalid formats carry a heavier penalty, lowering your grade significantly to ensure you pay attention to them.
Once issues are identified, we provide direct links to fix them. For example, if we find duplicates, one click takes you to the Data Cleaner. If we find sensitive PII, we direct you to the Data Anonymizer. The goal is to move from 'Audit' to 'Action' instantly.
No. For the free tool, data is processed in-memory and discarded immediately after analysis. For Pro users using the S3 integration, data remains in your secure bucket and is only accessed by our engine during the audit process.
Yes! You can download a summary of the issues found. In the Pro plan, you get a detailed line-by-line report indicating exactly which rows failed which checks, making it easy for your team to remediate.

Stop Relying on "Gut Feeling"

Validate your data with precision. Catch errors before they break your dashboard or ruin your marketing campaign.

The AI Data Auditor gives any spreadsheet or CSV an instant health check. Instead of eyeballing thousands of rows, you get a quality score plus a prioritized list of exactly what is wrong — missing values, duplicate records, inconsistent formats, and schema problems — with a recommended fix for each. It is the fastest way to know whether a dataset is safe to analyze, share, or load into a downstream system.

How it works

  1. 1

    Add your data

    Paste a CSV or JSON sample, or sign in to upload a file or connect a Google Sheet.

  2. 2

    AI profiles every column

    It measures completeness and uniqueness and scans for type mismatches, outliers, and structural issues.

  3. 3

    Get a scored report

    You receive an overall health score with completeness and uniqueness metrics broken out per column.

  4. 4

    Fix and re-check

    Each issue links to the right tool — send messy fields to the Cleaner or duplicates to dedupe — then audit again to confirm.

Use cases

Pre-analysis sanity check

Analysts validate a dataset before building a dashboard so a bad source never silently skews the numbers.

Vendor & partner data intake

Ops teams score every inbound file from suppliers or partners to catch broken exports before they enter the warehouse.

Migration readiness

Before a CRM or ERP migration, audit the export to surface schema gaps and integrity issues that would fail the import.

Recurring data QA

Run the same monthly extract through the auditor to detect regressions in upstream pipelines early.

Why DatumFuse

Objective health score

A single, repeatable number to track data quality over time instead of subjective spot checks.

Issue-level recommendations

Not just "this is bad" — a concrete next action for each problem it finds.

No setup, no SQL

Works on a pasted sample in seconds; no scripts, profiling libraries, or warehouse access required.

Privacy-respecting

Your data is processed to produce the report and is not used to train third-party models.