Data Quality (DQ) Tools

PiLog's Intelligent Data Quality Management solution provides end-to-end Data Quality Management for enterprises. it automates standardization, cleansing & management of unstructured/free text data by utilizing ASA (Auto Structured Algorithms) built on PiLog's taxonomy and the catalog repositories of master data records. It also provides pre-configured templates, Auto Assignment of Class & Characteristics, and is fully compliant with ISO 8000, UNSPSC, and various other standards.

SAS software for data preparation and data quality enables data transformation, self-service data integration and data enrichment for clean, reliable data. SAS Data Quality helps you make data-driven decisions you can trust. Use it to improve and monitor the health and value of your data so you can confidently fuel operations, compliance and analytics initiatives.

As an integral part of Talend Data Fabric, Data Quality profiles, cleans, and masks data in real time. Machine learning powers recommendations for addressing data quality issues as data flows through your systems. The convenient self-service interface is as intuitive for business users as technical users, fostering company-wide collaboration. Talend Data Quality delivers trusted data everywhere with easy onboarding, standards and rules application across all Talend integration platforms.

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.

RingLead offers a complete end-to-end suite of products to clean, protect and enhance company and contact information, leading to improved organizational efficiency, reliable business intelligence, and maximized ROI on CRM and marketing automation investments.

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.

Melissa Data Quality Suite leverages 35+ years of deep domain expertise in address management, data quality and identity verification to ensure your data is clean, accurate and fit for purpose. Easily validate, parse, standardize, match, and enrich customer data with global address verification, email validation, phone verification and name verification. With flexible on-premise and Cloud/SaaS deployment models, the Data Quality Suite is customizable to every environment and will empower your organization to unlock the full potential of your data.

Informatica Data Quality 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 success of your data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.

Alteryx provides a single workflow for data blending, analytics, and reporting. This workflow allows the seamless blending of internal, third party and cloud-based data, and simple analysis using 60+ prebuilt tools for spatial and predictive analytics. With Alteryx Machine Learning’s automated insight generation, you’ll quickly uncover hidden signals and key relationships in 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.