What is Data Quality?
Data quality describes the degree to which data fits the purpose it was intended for. Data is considered high quality when it accurately and consistently represents real-world entities and scenarios.
Save Costs & Time
Increase the effectiveness of matching algorithms and the accuracy of your golden records by profiling all contributing data sources to recommend validation and cleansing rules that can be applied in your MDM ingestion workflows.
Empower Citizen Users
Provide a low/no-code user interface and unified experiences for non-technical users to accomplish more with less. Simple intuitive browser-based UIs enable citizen users, data analysts, and data scientists to use a wide range of data quality services without the need for IT support and without wasting time on manual and repetitive data validation tasks.
Accelerate Cloud Migration Projects
Get the most out of your cloud investment by preventing bad data from entering it. Improve accuracy, reduce maintenance, and govern efficiently by adding data quality firewalls to data migration jobs. Improve the reliability and accuracy of data to result in only high-quality data.
Improve Business Outcomes
With data quality rules and API services, deliver only trusted data to decision points. Enable the desired business outcomes: growth, customer satisfaction & retention, process & resource optimization, cost reduction, risk mitigation, and increased shareholder value.
Promote Accountability
Enable collaboration between data managers and data consumers with up-to-date and reliable data quality metrics. With business users participating in data governance programs, everyone in the organization feels responsible for implementing data quality best practices and maintaining high data quality.
Profile, Classify & Score
Cleanse, Standardize & Enrich
Web UIs and Dev Toolkit
Cloud Enablement
Observability
