Data quality monitoring

Increase the trust in your data by implementing data quality rules and use automated monitoring to quickly discover any issues in your data. Easily track the issues, drill down to the specific location of the issue, and ensure efficient analysis over your data quality. Reduce the time spent manually analyzing your data and focus on utilizing high quality data to make business-critical decisions with confidence.

Increase trust in your data

Learn to trust your data and know how to use it to optimize business processes more effectively.

Data quality rules management

Create your technical quality checks and complex business rules. Set data quality thresholds to allow you to evaluate data quality results. Identify poor quality data effectively and automatically extract them to a pre-defined data system for further analysis and cleansing.

Data profiling

Get the context of your data and understand them. Measure basic data profiling characteristics and use them as inputs into your data quality rules.

Run monitoring

Start measurements at any point and at any level with completely automated, out-of-the-box job net monitoring. It provides information for performance optimization.

Visualization of results

Create dashboards to gain an overall summary of your data quality from multiple perspectives and quickly view trends in your data. Additionally, using gauges, results are visualized with defined thresholds to give you a quick and easy-to-read understanding of the state of your data quality.

Create hierarchies of your measurements

Analyze quickly the root cause of any problems in your data with logical groups of data quality rules. With unlimited levels of hierarchies, you can drill down from your dashboards to the most granular level of your data to find the true cause. Easily discover if the cause of the issue is part of your system or any source data system.

Data quality issue tracking

Create tickets and assign them to the relevant person to allow investigation and resolution of data issues in your system. Apply workflows to the ticket, discover the status of the issues, and monitor the history to know which systems or processes are causing issues most often.

Integration with external systems

Automate data quality monitoring by starting measurements by connecting to external scheduling systems. Set scheduling rules to run measurements according to your needs and Quality can automatically stop the processing if critical issues are found and notifications can be sent to relevant people to fix the issue.