Merge purge software
A highly customizable merge purge solution for attaining the golden record by detecting duplicates and designing prioritized list of merge purge rules that control master record selection and conditional record overwriting.
Trusted By
Trusted By
DEFINiTION
What is merge and purge?
A merge purge software screens all data records residing across multiple data sources, recognizes duplicate records, and allows you to build survivorship rules that automatically merge or remove duplicates.
As the average enterprise uses 65+ different data sources to store entity records relating to customers, vendors, or products, a merge purge software can add huge value to the process of creating a single source of truth for your organization.
Benefits
Why do you need a merge purge tool?
Overcome structural differences across datasets
Bring data together to resolve differences in terms of content (sematic and syntactic) and structure (data types and formats).
Use automated field mapping
Intelligently map fields and reduce the hassle of manually assessing and renaming fields across disparate sources.
Attain complete customer profile
Design personalized experiences by evaluating the holistic view of a customer’s behavioral patterns and preferences.
Control unique record selection
Create custom merge and survivorship rules for deciding the fields to be prioritized for unique record selection.
Avoid data loss during merge purge
Prevent data loss and ensure retention of the most accurate and comprehensive view of an entity after deduplication.
Streamline data-driven decision making
Uncover business insights that give an accurate, complete, and consistent view of brand image, perception, and experience.
Features
What DME’s merge purge software can do for you?
There’s more
What else do you get out of the box?
- Live preview of merged/purged data
- In-built data profiling, cleansing, and matching
- Unique and duplicate record selection
- Prioritized rules configuration
- Scheduler for automated merge purge
- Conditional merging and overwriting rules
- Color-coded view of merge purge operations
- Multi-format support for exporting results
User roles
A tool made for everyone

Data analysts

Business users

IT Professionals

Novice users
Features
We take care of your complete DQM lifecycle
Import
Connect and integrate data from multiple disparate sources
Profiling
Automate data quality checks and get instant data profile reports
Cleansing
Standardize & transform datasets through various operations
Matching
Execute industry-grade data match algorithms on datasets
Deduplication
Eliminate duplicate values and records to preserve uniqueness
Merge & purge
Configure merge and survivorship rules to get the most out of data
Want to know more?
Check out DME resources

Merging Data from Multiple Sources – Challenges and Solutions
Oops! We could not locate your form.

Linking Similar Records with Incomplete Data: Proven Approaches for High-Accuracy Entity Matching
Last Updated on December 29, 2025 If record linkage were as simple as matching names and emails, organizations wouldn’t be sitting on mountains of unleveraged

How Inaccurate Data Impacts Your Bottom Line
Last Updated on December 29, 2025 Most data problems don’t show up as dramatic failures. They appear as small problems or hide in plain sight.

Linking Similar Records with Incomplete Data: Proven Approaches for High-Accuracy Entity Matching
Last Updated on December 29, 2025 If record linkage were as simple as matching names and emails, organizations wouldn’t be sitting on mountains of unleveraged

How Inaccurate Data Impacts Your Bottom Line
Last Updated on December 29, 2025 Most data problems don’t show up as dramatic failures. They appear as small problems or hide in plain sight.

Unifying Data Across Silos: Build a Single Source of TruthÂ
Last Updated on December 24, 2025 Most companies don’t realize how much time they lose chasing basic facts. But research shows that decision-makers spend nearly 30% of their week (2.4 hours a day) searching































