Logical Dedupe
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Supported formats: .csv,.xlsx,.xls,.xlsm,.xlsb,.tsv
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About Logical Dedupe
Remove duplicates based on specific columns and rules.
Logical Dedupe removes duplicate rows based on a subset of columns you choose, rather than requiring every column in the row to match exactly.
This matters when two rows represent the same real-world record but differ in a timestamp, notes field, or other column that shouldn't count toward uniqueness, for example, matching only on email and order ID while ignoring the "last updated" column.
Category: Cleaning & PreparationCommon Use Cases
- Deduplicating customer records where only email should count as the unique key
- Removing repeat orders that share an order ID but have different timestamps
- Cleaning a mailing list down to one row per email address regardless of other field differences
Key Features
- Choose which columns count toward a duplicate match
- Keep first, last, or most-complete row when duplicates are found
- Processes large datasets without requiring exact full-row matching
- Reports how many duplicate rows were removed
Use Logical Dedupe when duplicates share exact values in key columns, and escalate to Fuzzy Dedupe when the same records instead have typos or spelling variants, then confirm results with Extract Unique Rows.
Frequently Asked Questions
Logical Dedupe lets you define which specific columns count toward a duplicate, instead of requiring every column in the row to match exactly.
They're removed from the output, keeping one row per unique combination of the columns you selected.
Load the CSV, choose the columns that define a duplicate (for example email only), and download the file with one row kept per unique key.
Built for anyone managing customer, order, or contact lists where duplicate records need a precise, column-specific definition of "duplicate."
Read the related guide →