Example: Finding duplicate entries

This example finds duplicate entries in the Contacts table using First Name & Last Name combinations. In the Companies table you may see how to prevent Company duplicate entries.
Example: Finding duplicate entries Database Illustration


The "Contacts (Finding Duplicate Entries)" table focuses on storing information related to individual contacts. Key columns include first name, last name, a count of duplicate occurrences, and standard fields for ownership and modification details. This table enables users to track and manage duplicate contact entries effectively. By storing duplicate counts, it aids in quickly identifying and consolidating duplicate records, ensuring that contact information remains accurate and streamlined.

The "Companies (Preventing Duplicate Entries)" table is dedicated to managing company records and preventing duplicate entries. It includes columns such as company name, phone number, email address, duplicate count, and standard fields for ownership and modification details. This table facilitates the identification and management of duplicate company entries within the database. By monitoring duplicate counts, it assists in maintaining a clean and organized database of company information, thereby enhancing data quality and operational efficiency.

The purpose of these tables is to streamline data management processes by proactively identifying and addressing duplicate entries. They provide a structured approach to ensure that contact and company records are accurate, reducing redundancy and improving the overall reliability of organizational databases. This database setup supports data governance efforts by enabling users to easily detect duplicates, merge records where necessary, and maintain a cohesive and reliable repository of contact and company information.

Also, there is an example displaying how to prevent duplicate entries. The Companies table comprises the validation rule that does not allow saving a new record if a new company name coincides with an existing one.

Here is the trick: create a Many-to-Many relation. The table refers to itself. Use Match Conditions to select the fields for duplicate finding. Then add a Summary column to calculate # of records (duplicates). When you have more than one, you have duplicates. Check the settings of the Duplicate Contacts relation for details.

To prevent duplicate entries, you should create a validation rule with the condition [Duplicate Count] is greater than 0. Moreover, you have to add the additional Match Condition Id<>Id to the relation. Due to this match condition, the system allows modifying existing records and saving changes. The example is adjusted in the Companies table.

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