Full CSV Data QA

Run end-to-end CSV quality checks with anomaly detection and filtering.

Intermediate~5 mincsvqaanomaly

Use case

Use this to enforce stricter QA gates on CSV datasets before handoff.

Workflow overview4 steps0 / 4 completed~5 min

What to expect

Follow the steps from left to right for a quick overview, then use the inline stepper below to run each tool.

Run end-to-end CSV quality checks with anomaly detection and filtering.

Current focusStep 1 · CSV Cleaner

0% complete

Step 1csv-tools Waiting

CSV Cleaner

CSV → CSV

Clean CSV

Normalized CSV ready for the next workflow step.

Step 2csv-tools Waiting

CSV Column Profiler

CSV → JSON

Profile CSV columns

Review the result here before moving to the next step.

Step 3csv-tools Waiting

CSV Anomaly Detector

JSON → JSON

Detect anomalies

JSON report with missing values, type errors, outliers, and duplicate keys.

Step 4csv-tools Waiting

CSV Filter

CSV / QUERY → CSV

Filter CSV

Review the result here before moving to the next step.

Workflow steps

Run this workflow inline

Work through each tool step here. Running a step automatically prepares the next step with the correct handoff value.

Workflow shortcut

Next unlocked step: Step 1 · CSV Cleaner

Progress is stored locally in this browser.

Step 1Ready to runcsv-tools

CSV Cleaner

Trim whitespace and normalize CSV records before conversion.

Open full tool

CSV input

Paste the raw CSV you want to normalize.

Cleaned CSV

Normalized CSV ready for the next workflow step.

Run this step to process the current input and prepare the next workflow stage.

Step 2Lockedcsv-tools

CSV Column Profiler

Profile CSV columns with inferred type, emptiness, uniqueness, top values, and numeric percentiles.

Open full tool

Complete the previous step first

This step unlocks automatically after all earlier workflow steps are completed successfully.

CSV input

Provide csv input for this workflow step.

Column profile report

Review the result here before moving to the next step.

Run this step to process the current input and prepare the next workflow stage.

Step 3Lockedcsv-tools

CSV Anomaly Detector

Identify data quality issues in CSV: missing values, numeric outliers (IQR), type inconsistencies, and duplicate key rows.

Open full tool

Complete the previous step first

This step unlocks automatically after all earlier workflow steps are completed successfully.

Anomaly detector input (JSON envelope)

Provide { "csv": "...", "numericColumns"?: ["age"], "keyColumn"?: "id" }.

Anomaly report

JSON report with missing values, type errors, outliers, and duplicate keys.

Run this step to process the current input and prepare the next workflow stage.

Step 4Lockedcsv-tools

CSV Filter

Filter CSV rows by column conditions.

Open full tool

Complete the previous step first

This step unlocks automatically after all earlier workflow steps are completed successfully.

CSV input or filter envelope

Use raw CSV, or provide { "csv", "column", "operator", "value" } for explicit filtering.

Filtered CSV

Review the result here before moving to the next step.

Run this step to process the current input and prepare the next workflow stage.