Data cleansing
Lesson 1 / 6
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Lesson outcome
I can describe the need for data cleansing and apply data cleansing techniques to a data set.
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Data cleansing involves detecting and correcting, or removing, corrupt or inaccurate data.
Data cleansing is important because real-world data is often messy, with errors or missing information.
Once the data is clean, charts or graphs can be created to help understand patterns and trends.
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This content is by Cashar and published under an open licence.