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.
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:
- special characters lost in the transfer from another source
- various formats of dates, telephone numbers or postal address
- use of abbreviations
Determine standardization rules and apply them to all the fields of your database.
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 Servic
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.