Data Quality
Top Melissa Data Quality Suite Alternatives and Competitors

The PiLog Data Quality and Governance Suite is a solution for Material, Service, Vendor, Customer, Assets, Employee, etc. with embedded Data Quality Management. It is a multi-domain, multi-lingual solution to create and maintain all the master data records in a single installation. One of the primary functions is that of Master Data Management with governance processes specific to creation, change, extension, deletion, and archiving to manage the complete life cycle of the master data records.

SAS Viya (formerly SAS Visual Data Mining and Machine Learning) is a cloud-native, end-to-end data and AI platform that makes development easier and boosts productivity with tools that are friendly for everyone on your team. Solve the most complex analytical problems with a single, integrated, collaborative solution – now with its own automated modeling API.

Talend offers robust data integration in an open and scalable architecture to maximize its value to your business. Simple, graphical tools and wizards get you up and running quickly with native code generation and Continuous Delivery capabilities that streamline development.

SQL Server Data Quality Services (DQS) is a knowledge-driven data quality product. DQS enables you to build a knowledge base and use it to perform a variety of critical data quality tasks, including correction, enrichment, standardization, and de-duplication of your data. DQS enables you to perform data cleansing by using cloud-based reference data services provided by reference data providers. DQS also provides you with profiling that is integrated into its data-quality tasks, enabling you to analyze the integrity of your data.

Unlock meaning from all of your organization’s data – structured or unstructured – with SAP Data Services. This data management software provides best-in-class functionality for data integration, quality, cleansing, and more. Ensure end-to-end support for growing data quality needs across users and data types with AI-driven automation.

Oracle Enterprise Data Quality provides a comprehensive data quality management environment, used to understand, improve, protect and govern data quality. The software facilitates best practice Master Data Management, Data Governance, Data Integration, Business Intelligence and data migration initiatives, as well as providing integrated data quality in CRM and other applications and cloud services.

Informatica Data Quality & Observability empowers your company to take a holistic approach to managing data quality across your entire organization. With Informatica Data Quality, you’ll be able to ensure the success of your data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.

Experian Aperture Data Studio (formerly Pandora) is an intelligent self-service data quality and enrichment platform that can be deployed in both cloud hosted and on premise environments. It unlocks the power of data to create opportunities for consumers, businesses, and society. Aperture Data Studio is a powerful and easy to use data management suite that helps you manage consumer data projects with confidence, in your own environment.

Global IDs provides software for Enterprise Information Management (EIM) and helps large enterprises organize their data ecosystems. The platform, Data Ecosystem Evolution Platform, has evolved for two decades, and is unique in its ability to scale and uses Machine Learning and AI to automate complex processes. The Global IDs platform maintains an up-to-date, comprehensive inventory of data assets, wherever they are in the ecosystem.

Automate revenue operations from data to action Maintain clean CRM data, automate lead routing, and trigger workflows based on buying signals and business logic with ZoomInfo Operations.

Alteryx One connects data, business context, and AI for insights that lead to confident decisions. Intelligent enterprises connect data, analytics, and AI across operations for faster, smarter decisions. With Alteryx One, analytics and AI show up where work happens, not just in slides. IT sets the guardrails as teams move faster and new ideas spark. From first use case to broad rollout, you get one step closer to becoming an intelligent enterprise.

ChainSys is an innovator in Master Data Management (MDM), Data Quality, and business platform implementation (ERP) space. Our success is largely attributed to the fact that we understand the core of how businesses work and the importance of ensuring all business units work smoothly together.

IBM InfoSphere® QualityStage® is designed to support your data quality and information governance initiatives. It enables you to investigate, cleanse and manage your data, helping you maintain consistent views of key entities including customers, vendors, locations and products. The solution helps you deliver quality data for your big data, business intelligence, data warehousing, application migration and master data management projects.

Validity DemandTools is the secure data quality platform that enables organizations to clean and manage Salesforce data in less time, enabling everyone to do their jobs more effectively, efficiently, and profitably. Manage your data – duplicates, standardization, record reassignments, lead processing, and more – in record time and deliver high-quality data across your business.

Cloudingo is a cloud-based deduplication and data quality application built specifically for Salesforce. Cloudingo is a fully customizable, easy-to-use platform that makes the pain of cleaning and managing Salesforce data a thing of the past. Cloudingo finds duplicates using user-defined filters. Start with prebuilt filters then create more with the drag-and-drop user interface.

Ataccama enables enterprise data democratization with a unified platform for automated data quality, MDM, and metadata management across cloud and hybrid environments. We enable business and data teams to collaborate on creating high quality, reusable data products and massively scale data-driven innovation while maintaining data accuracy, control, and governance.