Modern stacks are complicated, making it hard to keep track of data quality.   

Luckily, there’s a solution. Collibra Data Quality & Observability monitors data quality and data pipeline reliability to help you rapidly remediate anomalies.  

Join Hariprasad Ashwene, Senior Sales Engineer, at Collibra, to see how Collibra Data Quality & Observability leverages machine learning to generate adaptive checks and rules that proactively identify data quality issues across a variety of databases, files and data streams. Predictive, continuous, and self-service data quality helps rule writers focus on high-impact tasks such as eliminating the root causes of data errors, and helps business users access high quality data for their analytics and AI modeling work.  

He’ll explore how to:   

• Get started with Collibra Data Quality & Observability  
• Create data quality rules using AI/ML  
• Identify quality issues that traditional rule engines would miss 

Website: https://www.collibra.com/