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AI & Big Data Expo Conference Information

Join Pandata and over 250 other experts at this year’s event.

AI & Big Data Expo Overview

Let's Meet at AI & Big Data Expo

The AI & Big Data Expo is the premier event for enterprise professionals interested in leveraging artificial intelligence strategy and technology to grow their businesses.

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With an agenda of over 250 innovative speakers and sessions available both in-person and online, the Expo promises to deliver actionable takeaways for a wide range of industries. For more information and to register for the event, held October 5-6, 2022 in Santa Clara, CA, visit the AI & Big Data Expo website.

Proud Gold Sponsor of the 2022 AI & Big Data Expo

At Pandata, our mission is to cultivate lasting, strategic partnerships with a variety of organizations, helping them proactively design AI that can be trusted.

AI & big data expo sponsor

We believe that AI developed with transparency, privacy, and ethics in mind should be employed by all industries—which is why we’re proud to be a Gold Sponsor at AI & Big Data Expo, an event that advocates for the need for trustworthy AI in industries from government to retail and beyond. 

To view other events Pandata has either sponsored or attended, visit our Conferences & Events page. 

Must-See Session, Hosted by Pandata CEO Cal Al-Dhubaib

Pandata CEO and AI Strategist Cal Al-Dhubaib is joining the lineup of expert speakers and instructors presenting during the AI & Big Data Expo. Catch his session on Day 1, Oct 5, at 2:20 p.m. PDT.

Generating Business Value with Applied Machine Learning and AI 

While AI continues to evolve at a rapid pace – adoption rates growing day over day – projects still fail at a disappointingly high rate.

In the past, capturing data at scale and building models was the challenge, but today we’re confronted with the issue of making AI more robust while avoiding the risk of unintended consequences. While the tools are new, many challenges remain the same.

This session will cover:

  • Building blocks to develop requirements for AI-driven projects.
  • Examples of identifying and mitigating project risks and unintended consequences.
  • How to build the business case for an AI project (and get buy in).