In today’s rapidly evolving digital landscape, AI/ML have become essential requirements, reshaping industries, driving innovation, and accelerating informed decision-making. However, the success of these transformative technologies hinges on a crucial yet often overlooked foundation — data integrity.

Faulty, biased, or incomplete data can derail your AI initiatives, embedding errors that perpetuate themselves across models and decisions.

In this webinar you’ll learn:

• How poor data quality can impact AI/ML outcomes, including biases and inaccuracies.
• Strategies for implementing end-to-end data integrity testing to safeguard your AI/ML pipelines.
• How enterprises can effectively prepare for their AI/ML journeys, from establishing data management practices to addressing potential risks early.

Speakers:

• Curtis O’Dell, Business Performance Director, Data Integrity
• Ben Simo, Principal Product Manager