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.

Improve MDM Results
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.

Maintain Quality as You Evolve
Avoid costly overruns using advanced profiling, cleansing, and standardization capabilities as you upgrade to a new SaaS suite, move on-premises applications to the cloud, restructure data warehouses, or add new capabilities between applications.

Reduce the Data Prep Burden
Consistently cleanse, standardize, deduplicate, and enrich raw data sources, providing business-ready datasets that drive all human and automated business decisions.

Consistently Enforce DQ Standards
Improve accuracy, reduce maintenance, and govern efficiently by implementing a data quality firewall. With a catalog of re-usable APIs, you can consistently verify, correct, and enrich data right at the point of entry.