Automated Data Quality Monitoring and Testing
Goodbye to manual tests. Hello to automated data quality monitoring and testing of your data
Why Is Quality Data Important?
Quality data is a mission-critical requirement for virtually any modern enterprise. Because data quality issues can disrupt business processes and services, invalidate any type of analytics performed in the company and damage a company’s resources, revenue & reputation. However, despite the importance of data quality, it is still woefully undervalued, and significant room for data quality improvement still exists in most enterprises.
Automated Data Quality is scalable and easy-to-extend data quality solution which helps to:
- Define data quality expectations for data
- Integrate with a wide range of data sources
- Validate data
- Report and visualize issues
Automated Data Quality can be used for the below solutions across different verticals
- ETL / ELT data testing
- Data warehouse data testing
- Data migrations testing
- Bigdata, Datalake / Datalakehouse data testing
- NoSQL data testing
- Datamesh data testing
- Continuous testing with Devops for data
- Data Contracts enforcements
- Data observability and eliminate data downtime
