Data deduplication and deduping to improve your database quality.

Last Update : 18.04.24 • Publication : 01.12.22 • Reading :

Redundant data are a scourge for your database. Duplicates display a bad image of your company: contacting the same person several times by mistake is not very professional. Duplicate data increase the weight of your database and increase storage costs. In addition, duplicates can distort your reporting since a client is listed in several different places. For the health of your database and your company, it is important to deduplicate and dedupe your data as often as possible.

Deduplication, Deduping: how are they Different?

Deduplicating and deduping data are not exactly the same thing. However, both operations aim at identifying, merging, and removing redundant data in your databases.

  • Deduplication - Deduplication is the process of searching for similar data across multiple files. These data are called duplicates.
  • Deduping - Deduping is the detection and removal of similar data within a file. These data are called dupes.

How to Remove Redundant Data from your Files?

Tackling dupes and duplicates can be a daunting task. The larger your database is, the longer and harder this task will be. You can perform data deduplication and data deduping in 3 steps: normalization, consolidation, and manual or automatic check.

Data Normalization

Redundant data are often caused by non-standardized information.

In your databases, you will certainly find customers listed several times because of encoding or importing errors:

  • Typos
  • special characters lost in the transfer from another source
  • various formats of dates, telephone numbers or postal address
  • use of abbreviations
  • etc.

Determine standardization rules and apply them to all the fields of your database.

Data Consolidation

Storing your customer and prospect information in several different files is the best way to end up with duplicate data. Gather all your data in the same place. Use a CRM or database management system more complex if needed.

Today, software programs allow you to use data easily without advanced computer knowledge. After a short training, your employees will all be able to use it.

Manual Processing or Automated ServicE

When you have normalized and gathered all your data, it is time to hunt for redundant information. To do so, you have two options: manual check, or a specialized tool.

If you choose the manual check, you can simply use a spreadsheet such as Excel. If you have a small volume of data to correct, this is feasible. For larger files, create SQL queries to detect and merge duplicate lines.

Checking your database line by line is a tedious task, even with good SQL queries. Some companies specialize in database enhancement; they can help you. They offer, among other services, database cleaning and enrichment.

Do not let duplicated data and redundancy impact the quality of your database. Act before this redundant information harm your business. Standardize your data, consolidate your files, detect, remove, and merge all duplicate lines. This is imperative to ensure that your database remains an essential ally for the expansion of your business.

What is Data Management?
Data management is one of the most important disciplines for making business decisions and conducting activities that will benefit the business.

Why is it important? What processes should be in place? What are the best practices? Here's everything you need to know about it.
Marc Wahba
Author Marc Wahba

Meet Marc, the co-founder and CTO of Infobel. He is in charge of software development. In 1991, he obtained a degree in civil electromechanical engineering from the Polytechnic Faculty and later earned a master's degree in management from the Solvay School of Brussels. Along with his brother, he founded Infobel in 1995, which was the first online directory to offer an online white pages directory. Marc's innovative mindset has led to the launch of new data products and services that have become a global success, serving clients all over the world.



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