Melissa Automates Clean Data Processes with Intuitive Customer Data Validation Platform

Unison reduces strain on SQL developers by empowering data stewards to manage operations – no programming expertise required

Melissa, a leading provider of global data quality and address management solutions, announced its Unison customer data verification platform as an easy-to-deploy solution for data stewards to maintain impeccable customer data. Unison brings together all of Melissa’s data quality API capabilities including global address, name, phone, email verification, geocoding, and data matching, into a flagship UI that is fast, scalable, and requires no programming. Advanced, proprietary fuzzy matching algorithms with golden record/survivorship rules are built in and controllable through a simple, intuitive interface.

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“When dealing with customer data, SQL Server developers face common issues such as unwieldy packages, system updates, extensive vendor options, and version control which exacerbate already complex automation and rapidly evolving processes,” said Bud Walker, vice president, enterprise sales and strategy, Melissa. “With Unison, data stewards are instead directly empowered to validate, cleanse, import, and export data via an intuitive, project-oriented framework, freeing their developer colleagues to tackle higher value tasks.”

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Unison offers flexibility through a data-agnostic technology stack, connecting disparate data streams to quickly verify, enrich, and unify customer profiles with accurate, up-to-date data. The platform is scalable across limitless nodes, with flexible collaboration, scheduling, and rights management. Its architecture capitalizes on existing computer assets, disseminating customer data quality jobs across the enterprise and harnessing the processing power required to quickly render contact data clean and reliable. Scalable to accommodate huge datasets and multiple secure users, Unison also offers visual analytics, detailed logging, and audit trails for stewards and stakeholders alike.

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