ON-DEMAND WEBINAR PANEL

How to Align AI & BI to Business Outcomes

FEATURED SPEAKERS | DATA & ANALYTICS LEADERS
Juan Gorricho headshot
Juan Gorricho

VP of Global Data Business Intelligence, Visa
Ram Kumar headshot
Ram Kumar

Chief Data and Analytics Officer, Cigna
Greg Coquillo, Ai Technology Manager, Amazon
Greg Coquillo

AI Technology Manager, Amazon
Aruna Pattam Hcl
Aruna Pattam

Head of AI & Data Science, HCL Technologies
Dave Mariani headshot
Dave Mariani

Chief Technology Officer, Founder, AtScale

Your Moderator

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Get practical advice from Global 1000 data leaders at Visa, Cigna, Amazon, and HCL Technologies on how they are aligning AI & BI toward business outcomes at their organizations.
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Now available on-demand!

Join leaders from Visa, Cigna, Amazon, & HCL Technologies for presentations on how they are accelerating business outcomes with AI & BI across their organizations.

You’ll learn how they are leveraging Machine Learning and Big Data Analytics to drive business value. They will dive deep into their strategies to define goals, hypotheses, questions, and KPIs that will help their companies identify and measure the best areas of impact for AI & BI.

Our panelists will share practical guidance on how they are working to close gaps between data science and BI teams to combine predictive analytics with descriptive analytics in a single platform to develop sustainable business outcomes.

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In this webinar

You will learn about:

  • Using AI and Data Science at scale in order to solve business challenges.
  • Leveraging Machine Learning and Big Data Analytics to design predictive models that enhance business decision-making.
  • Implementing the right processes and tools to democratize data and empower individuals to utilize data through self-service analytics.
  • Delivering Augmented Intelligence to a broader audience by publishing the results of data science programs through existing BI channels.
  • Feeding data science models results back into the semantic layer to consume predictive insights alongside historical data.
  • Laying a scalable foundation for AI & BI with your data architecture.
  • Gaining speed of thought query performance and consistent KPIs across all of their BI/AI tools.
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Who should watch

AI, BI, and Data leaders (e.g., Chief Data Officers, data scientists, data literacy, business intelligence, and analytics professionals) looking to make AI & BI work at scale.