Eliminate Dirty Data

Improve Data Accuracy in Record Time

Most organizations utilize a variety of systems and applications across multiple divisions, yet many of these tools don’t necessarily communicate with each other. Data entered or updated in one application may not find its way to another application, causing duplicate data and errors that can seriously impede business decisions and cause a host of other issues. Data quality is critical, yet manual attempts to remove duplicate data are time consuming and risky, and many data quality tools are expensive and complicated to use.

Data MatchMerge Overview

Pervasive Data MatchMerge™ is data quality management software designed to automate the data scrubbing process by identifying and merging duplicate data across large data sets to generate a new golden record. Leverage customizable algorithms with an easy-to-use yet powerful interface to de-dupe data across the organization at a price that will fit your budget. The flexibility of Pervasive Data MatchMerge™ enables it to easily incorporate third-party data cleansing and standardization applications through standard APIs. This powerful combination yields an intuitive, highly accurate and fast solution for identifying and resolving duplicate data problems.

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Benefits

Pervasive Data MatchMerge™ offers:

• High performance and fast response times that scale for large data sets
• The ability to match on any combination of fields
• “Fuzzy” matching to identify similar duplicates
• Multiple algorithms and encoding methods for better results
• Easy property configuration management to fine-tune matching parameters
• Output in groups with metadata to facilitate downstream processing
• Integration with Pervasive Data Integrator and third party applications
• Integration with daily workflows

If you‘re looking for true data quality as part of a comprehensive data management solution, let Pervasive show you how Data MatchMerge™ can provide data cleansing for ultimate data accuracy. Contact us at 1-888-296-5969 to get started.