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Choose the right Tool

Start with the Tool that matches your actual task.

Quick decision guide​

If you want to...Use this Tool
standardize messy valuesCleaner
keep only Records that match RulesFilterer
remove repeated RecordsDeduplicator
check whether values meet requirementsValidator
translate values from one form to anotherMapper
hide or mask sensitive valuesObfuscator
understand the shape and quality of a datasetData Profiler
combine Records from two datasetsJoiner
divide one dataset into separate outputsSplitter
calculate counts, totals, averages, or distributionsStatistics

Common examples​

I have inconsistent values in the same Field​

Use Cleaner.

I need only a subset of the File​

Use Filterer.

I suspect the File contains repeated Records or repeated entities​

Use Deduplicator.

I need to check whether required Fields or allowed values are correct​

Use Validator.

I need to convert codes, labels, or categories into another format​

Use Mapper.

I need to reduce exposure of sensitive values before sharing a File​

Use Obfuscator.

Obfuscator can mask, randomize, or replace selected Fields while keeping the dataset structure available for review.

I need a quick picture of completeness, distributions, and data quality signals​

Use Data Profiler.

I need to combine Fields or Records from two datasets​

Use Joiner.

I need to separate one dataset into multiple files or groups​

Use Splitter.

I need numeric summaries, counts, totals, averages, or distribution insights​

Use Statistics.

When one workflow may use more than one Tool​

A real-world process may involve more than one step. For example:

  • profile a dataset before doing anything else
  • clean inconsistent values
  • validate important Fields
  • join related data from another File
  • split the result into separate outputs
  • calculate summary statistics
  • obfuscate sensitive Fields before distribution

Tip for new users​

When you are uncertain, start with Data Profiler or a small test Run in the Tool you think is most likely to fit. Reviewing a small output early usually clarifies the next step.