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Data & Analytics · Foundational

Data Cleansing

Detecting and correcting or removing inaccurate, incomplete, duplicate or improperly formatted data.

Definition

Typical tasks include trimming whitespace, fixing case, standardizing formats, handling nulls, removing duplicates, correcting typos and validating against reference data. Each change should be documented for reproducibility.

Example

TRIM(UPPER(country_code))

Exam tip

Cleanse in a repeatable pipeline step, not by hand-editing source files.

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