Cleaning Data
Definition
Cleaning data is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in a dataset. It involves tasks like removing duplicate entries, handling missing values, and standardizing formats to ensure data quality.
Analogy
Imagine you have a messy room with clothes scattered all over the place. Cleaning data is like tidying up your room by folding clothes, organizing them in drawers, and getting rid of any unnecessary items. The goal is to have a clean and organized space where everything is in its proper place.
Related terms
Data Validation: The process of ensuring that data meets certain criteria or rules defined by the user or system.
Data Preprocessing: A set of techniques used to prepare raw data for analysis by transforming it into a consistent format suitable for further processing.
Outliers: Data points that significantly deviate from the normal pattern or distribution within a dataset. Identifying outliers is an important step in cleaning data as they can affect statistical analyses.
"Cleaning Data" appears in:
Study guides (2)
Practice Questions (1)
- How can cleaning data help in dealing with non-uniformity?
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