Why large data sets need cleaning, and how to go about it
Finnegan Pierson
In a business context, analyzing data can be incredibly important, but it can also be a drain on resources. Processing data into something useful is becoming an increasingly difficult job as data becomes more and more abundant. Because of this, cleansing or scrubbing your data is vital, even though it can be a time-consuming process.
In any large set of data, there are going to be entries that don’t meet the quality standards they should. This could be because data is missing from the entry, because entries are duplicated or because the person or program recording the data made an obvious mistake.
Generally, in companies where data is routinely scrubbed before analysis, it is the job of the analysts to clean up all their own data sets. While having your employees manually clean data is not a bad approach, paying for a professional data scrubbing service can free up time and money
Once your data has been scrubbed, you should get much clearer and more actionable results from analysis.. If you are dealing with large sets of data, scrubbing your data sets is an essential step in obtaining clear, useful results.
If you decide to keep the task in house, you can make the job simpler for your analysts by creating a standardized or automated data collection process and by making sure the data you collect is going to help you answer the questions you have.