Active Data Quality
for the Enterprise

Helping enterprises proactively manage their full data quality lifecycle through contextual data quality checks, anomaly detection and remediation.

Machine Learning

Leverage the power of full lifecycle automation for anomaly detection in your data ecosystem with Qualytics’ embedded artificial intelligence.

Data Quality Rules

  • Auto infer 85% of data quality checks using historic data.
  • Continuous optimization for evolving data quality needs.
  • Rules enforced across all the Qualytics 8 categories.
  • Author custom rules for 100% coverage.

Anomaly Detection

  • Periodic and ongoing monitoring for anomalies in data sets
  • Advanced detection to identify and flag anomalous data values or patterns.
  • Uses feedback to continuously adjust detection thresholds and tolerance for accurate alerts.


  • Expose anomalies and metadata to help teams to help teams take corrective actions.
  • Automatically trigger remediation workflows to resolve errors quickly and efficiently.
  • Maintain high data quality and prevent errors from affecting business decisions.
  • Recover valuable time needed for manual intervention.

The Qualytics 8

Qualytics uses these 8 fundamental categories
to assess data quality.


Required fields are fully populated


Availability and uniqueness of expected records


Alignment of the content to the required standards, schemas, and formats


The value is the same across all datastores within the organization


Your data is the resolution that is expected – how tightly can you define your data?


Data is available when expected


Data has the same size and shape across similar cycles


Your data represents the real-world values they are expected to model


Qualytics fits seamlessly into your data stack.