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Eliminate Duplicate Data: A Guide to Cleaner, More Accurate Spreadsheets

Writer's picture: Surender Thandalai NatarajanSurender Thandalai Natarajan

Duplicate records - this is the most common problem that every one of us has faced while using any kind of data.




Definition

Duplicates are identical or nearly identical entries that appear multiple times within a dataset. These entries usually contain the same or very similar data values in one or more fields.


A unique record can be defined using a single or multiple fields. A simple example would be the combination of First and Last names.


Types of Duplicates

  1. Exact Duplicates:

    • These are records where every field is identical across multiple entries.

      Example:

      • A customer database has two records with the exact same name, email address, phone number, and other details.

  2. Partial Duplicates:

    • These records share certain key fields in common, but other fields may differ. There is a minor difference between the records. Partial duplicates can happen if, for example, a person is entered twice with minor variations.

      Example:

      • A record has the same name and email but a slightly different phone number due to a different formatting.

      • One entry might read “John Doe” and another “Jon Doe” with the same email address.

  3. Fuzzy Duplicates:

    • These records are not identical but are close enough to indicate they may refer to the same entity. Fuzzy duplicates can result from variations in spelling, abbreviations, or data entry errors.

    • Example:

      • "Johnathan Smith" and "Jonathan Smith" might refer to the same person but are slightly different in spelling.


Removing Duplicates

Everyone wants to capture and remove these duplicates for further processing or analysis of data for the decision-making process. Though removing duplicates looks simple, in a business context it gets complex.


For example in an email marketing list, when you have an email that is present more than once. This data is captured with the materials purchased and total amount spent and the last date of the transaction. Now for an effective marketing campaign, a marketing person may want the latest email record. In this, we need to keep the last occurring duplicated and delete other instances of the email record.


In another example, the most common issues of duplicates exist in CRM systems. Usually, a CRM has access to multiple sales associates and they end up updating the same name because of various reasons. In the end, a sales analyst or CRM administrator ends up cleaning the records.


The issue of the duplicates is endless.

We have recently developed a tool that helps you to remove duplicates from your spreadsheet.

You can define the uniqueness of the record using multiple columns and even select which occurrence of the record you want to keep (first or last ) and make your data duplicates free.



Do let me know your feedback.





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