What is “data cleaning” and why do it?
Almost every organization has missing, incomplete, duplicated, inaccurate or otherwise unreliable records in their spreadsheets or database. In order to work with that data to produce meaningful information those records have to be repaired or deleted - “cleaned” in other words. Doing that by hand is time-consuming, error-prone and expensive and creating a program to do the work requires coding expertise. Now however, there are no-code platforms that can help businesses repair their data automatically, without doing any program coding.
What is “cleaned” data used for?
In recent years more and more organizations are using their accumulated historical data to create data visualizations and to train machine learning models. Errors in the input data due to missing, incomplete or invalid fields will lead to invalid or inaccurate results from machine learning models trained on that data.
How does a no-code data cleaning site work?
Generally you import your raw data, make sure all the columns are showing with the correct type of data in each column, and then you select to start cleaning. At that point you can normally set up cleaning rules or "transformations" for each particular column. A cleaning rule might be "Remove duplicate values" or "Replace any missing values with the word 'Unknown'" or "Remove any rows with a value over $999 in this column". Once the data has been cleaned you can visually spot check it to make corrections manually or to make sure that you didn't leave out any necessary transformations. Then you should be able to export the cleaned data as a CSV file that can be used as input for a "no-code" machine learning platform.
Where can I find a no-code data cleaning platform?
There are a number of platforms that allow you to clean raw data without needing to do any coding. Probably the most complete platform at the moment is Amazon Web Services' Glue DataBrew; you can find a detailed explanation of how it works and what options you have available with it at:
https://aws.amazon.com/blogs/aws/announcing-aws-glue-databrew-a-visual-data-preparation-tool-that-helps-you-clean-and-normalize-data-faster/