Collibra Data Quality & Observability best practices for reliable data pipelines

Artificial Intelligence (AI) and analytics requires high quality data to ensure reliable outputs and accurate decision making. The data quality rules needed for ensuring reliable data evolve as data moves from ingestion and storage, to compute and consumption. This webinar will cover best practices to ensure the right data quality rules at the right points in your data pipelines. The demonstration will show how AI can automate and simplify the creation of rules for monitoring and management of data health to ensure reliable AI and accurate analytics.

During this webinar you’ll learn how to build and manage data quality rules for:

• Data ingestion from source systems and files
• Data stored in data warehouses and lakes
• Data consumed in AI and analytics processes

We're excited to invite you to an insightful Ask Me Anything session following the webinar. Use this opportunity to connect with Kirk Haslbeck, Field CTO, Data Quality and Dan Everett, Senior Product Marketing Manager, at Collibra. This Q&A promises invaluable insights and an open forum for all your questions.