Following the collection of data through a survey or other research method, data must be cleaned. The data cleaning process, also known as data scrubbing or data cleansing, can have a huge impact on the reliability and validity of your final data, as it ensures that you are only using the highest-quality data to perform your analysis. By rushing or eliminating the data cleaning step, you run the risk of including false, misleading, or duplicated records in your final dataset. Following a thorough data cleaning process will minimize errors made due to data that is formatted incorrectly.
In this episode of GeoPoll talks, Roxana Elliott talks to Benard Okasi, GeoPoll’s Director of Research, about why data cleaning is important and the data cleaning process.
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