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

Qualytics uses your historic data to automatically infer rules that identify anomalies in existing and new data. These rules evolve as your data evolves, ensuring that your data quality is continuously optimized and adapted to changing business environments.


Anomaly Detection

With broad support for your team’s desired monitoring, notification, and data management layers, Qualytics facilitates rapid response cycles and incorporates your teams’ anomaly assessment resolutions into feedback that informs continuous tolerance adjustments – ensuring the correct balance of signal to noise.


By exposing anomalies and the metadata around them, Qualytics empowers teams to take corrective actions in their data pipelines.


Automatically triggering remediation workflows for specific types of errors and ensuring that issues are resolved quickly and efficiently.

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.