Data Quality

Profile, validate, and fix all your enterprise data

The increasing variety and volume of available data has the power to improve decisions at all levels of the modern enterprise—if you can trust it.

Inconsistency in the quality of that data can have the opposite effect, and erode trust in its use for decision-making.

Ensure your data is fit for purpose—for validating and correcting the data that feeds operational and analytical applications, enhancing system migration and software integration projects, and implementing more effective master data management initiatives. Build trust in your data for better enterprise-wide decisions.

What is Data Quality?

Data quality is achieved when data fits the purpose it is intended for. High-quality data accurately describes real-world entities and scenarios.

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Benefits
Improve Customer Relationships

Improve Customer Relationships

Market leaders across industries know that the key to better customer relationships is personalization and service. Improve the accuracy of your customer data with deduplication, cleansing, and standardization—then enrich it using third-party address, email, and phone verification services that improve your knowledge and ability to deliver flawless service.

Implement a Data Quality Firewall

Implement a Data Quality Firewall

Address data inconsistencies and errors before they pollute downstream systems. Implement consistent and reusable data quality services that profile, verify, and cleanse data when it enters your network through apps, streams, message queues, and batch interfaces.

Enable Data Governance and Compliance

Enable Data Governance and Compliance

Support data stewards in enforcing data governance policies and maintaining regulatory compliance with software that profiles, classifies, and automatically fixes problems. Use workflow-driven processes for managing anomalies requiring human intervention.

Democratize with Confidence

Democratize with Confidence

Further democratize data use and reduce IT burden by insulating business users from the complexity of cleansing and normalizing data. Apply standardized data quality processes and ensure that only reliable data is delivered at the right time to inform business decisions.

Capabilities
Profiling

Profiling

Quickly assess patterns and anomalies in any data source and determine missing, duplicate, and erroneous values.

Cleansing & Standardization

Cleansing & Standardization

Achieve higher levels of consistency and accuracy by concatenating, splitting, replacing, or removing non-standard values.

Enrichment

Enrichment

Augment the data you have with other internal or third-party sources to improve accuracy and completeness.

Matching & Deduplication

Matching & Deduplication

Identify duplicate records using deterministic and fuzzy matching techniques.

Remediation

Remediation

Facilitate collaboration between data stewards and IT with workflow-driven processes that address issues requiring manual intervention.

Monitoring

Monitoring

Measure the health of your data assets by tracking data quality KPIs over time to identify and address issues.