What file formats does the profiler support?

The tool supports CSV and JSON files. For JSON, the data should be formatted as an array of objects or an object containing a 'rows' array.

How is the overall quality score calculated?

The score is a 0-100 operational summary. It decreases based on the frequency of missing cells, duplicate rows, format drift, and numeric anomalies found in the dataset.

Can I check for duplicates using specific columns?

Yes. By entering comma-separated column names in the 'Duplicate Key Columns' field (e.g., 'id,email'), the tool will flag duplicate combinations based only on those business keys.

What does 'format drift' mean in the report?

Format drift highlights columns where the data structure is inconsistent, such as mixing different date formats or combining numeric codes with free-text strings.

How does the tool detect numeric outliers?

The profiler uses an Interquartile Range (IQR) style rule to identify and flag numeric values that fall significantly outside the normal distribution of a column.

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Data Analysis

Dataset Quality Profiler

Profile CSV or JSON datasets for missing values, duplicate rows, format drift, type inference, and numeric outliers

Details

What this tool helps you do

Paste a CSV dataset into "Dataset Input" or upload a CSV/JSON file. The profiler inspects each column and gives you a quick quality snapshot before the data moves into BI, ETL, or machine-learning steps.

What the tool checks:

Missing values per column
Duplicate rows, or duplicate combinations based on the columns you list in "Duplicate Key Columns"
Column type inference: number, boolean, date, string, or empty
Numeric outliers using an IQR-style rule
Format drift for string/date-like columns, such as mixed date styles or code-vs-free-text inconsistencies

How to fill the fields:

Dataset Input: paste CSV text directly when you want a quick profile
Dataset File: upload CSV or JSON if the dataset is larger or already saved locally
Duplicate Key Columns: optional comma-separated keys such as id,email to detect duplicates by business key instead of whole-row matching
Sample Rows: controls how many example rows appear in the report preview

How to read the report:

Quality score is a simple 0-100 summary where more missing cells, duplicate rows, and anomaly signals reduce the score
Missing shows how many blank/null cells were found in that column
Distinct shows how many unique values appear in the sampled dataset
Anomalies highlights numeric outliers
Format drift highlights columns where values look structurally inconsistent

Current scope:

CSV and JSON are supported
JSON should be an array of objects or an object with a rows array
The score is meant as a quick operational signal, not a formal data-governance grade

Execution

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Result

Ready for a run

Run the tool to preview files, text, structured data, or streamed output here.

Samples

Dataset Quality Profiler

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Key facts

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Use cases

Examples

1. Profile a transactional CSV before loading it into BI

2. Auditing a JSON user dataset for anomalies

FAQ

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