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Webinars

In depth presentations and panel discussions from IIA leaders, clients and experts on concepts, topics and trends essential for analytics and AI success.

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As organizations faced yet another year of whiplash – from post-pandemic planning to an unpredictable global economy – data and analytics leaders and their teams must consider what lies ahead for the benefit of their…

Building a sustainable data strategy requires cross-organizational alignment that is difficult to achieve. In this session, Kathy Koontz, former Director of IIA’s Analytics Leadership Consortium, will explore people and process considerations an organization should account…

With the rapid advancement of digital technologies, it is impossible to design perfect rules, systems, or processes to manage AI ethics. They would be outdated the moment they were deployed. Instead, data and analytics leaders…

The benefits of AI for enterprise optimization and innovation are widely accepted and yet a paradox exists between AI’s potential and adoption: Survey data shows that up to 90% of AI/ML initiatives fail adoption; 70%…

Analytics and AI are booming in organizations, but many companies are not yet realizing strategic value from their projects and investments. One key reason for this lack of strategic value is the absence of an…

It’s one thing to promote an inclusive culture. But how do you actually live it? The tech field, in particular, has rightly been challenged to create more equilibrium between men and women at the level…

Bolstering the data and analytics skills of employees is critical for enterprises as they progress in their digital transformation efforts. But data literacy is not a one-size-fits-all affair. Successful organizational upskilling for data, analytics, and…

Overview The research is overwhelming: The vast majority of analytics and AI models intended for internal consumption don’t get deployed. This die-on-the-vine feature (or bug?) of enterprise analytics impacts the economic value of AI investments…

For decades, all organizations operated within a data and analytics monolith. Delivery of data and analytics (or business intelligence) came from IT with underwhelming results due to complex infrastructures, delays, minimal UX, and lack of…