v1.3.0 - ADQ Release Notes
ADQ v1.3 introduces a host of features enhancing user experience, flexibility, and analytical capabilities, further bolstering the platform's capabilities and providing users with a comprehensive solution for data quality management.
Platform Overview: Detailed summary page provides insights into the underlying components and versions of the ADQ platform.
Rule Management: Ability to promote reusable and SQL rules across environments, facilitating seamless migration of DQ checks to production.
User Accessibility: Direct access to the ADQ user guide from the About page for easier navigation and reference.
Rule Flexibility: Extended flexibility in rule ID formats and default separator definition for smarter filtering.
Insights Navigation: Users can drill down to specific data quality issues from Insights for efficient problem-solving.
Data Connectivity: Added support for Snowflake, CSV, and Excel data sources for enhanced connectivity.
Authentication Integration: Integration with various authentication approaches, including SAML and OpenID Connect.
Workflow Efficiency: Bulk assignment of data quality issues to data stewards for streamlined resolution.
UI Enhancements: Improved user interface with RAG colour coding, simplified navigation, and toggle options for better user experience.
Rule Validation: Execute and schedule reusable rules suggested by profiling configurations for efficient rule validation and execution.
Error Handling: Improved error handling ensures the batch DQ process runs to completion, with detailed error messages for troubleshooting.
Machine Learning Highlight: Wand icons added throughout the UI to highlight machine learning components.
Performance Optimization: Backend optimization for faster retrieval of Advanced Insights data.
Outlier Detection: New functionality added to identify outliers in data using various statistical techniques.
SQL Rule Building: DQ Authors can now build SQL-based rules through a user-friendly wizard, saving processing time.