Given the ease with which AI-based initiatives can be executed nowadays, it is no surprise that more and more enterprises are considering adopting AI-powered autonomous analytics to make well-informed decisions more economically, improve operational efficiencies, and delight customers. Achieving the true promise of AI, however, requires access to data and the execution of such analytics in real time. Join this session to learn about data processing challenges and architecture patterns fueling AI-driven businesses.
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Speaker
Lalit Ahuja
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Lalit Ahuja is responsible for the direction, implementation and delivery of GridGain’s technology strategy. He works closely with GridGain customers and partners worldwide and leads the Engineering, Product Management and Delivery teams in ensuring GridGain products and services meet or exceed all customer expectations.In his career spanning over 25 years, Lalit has led various IT functions including enterprise architecture, product management, large scale program management, and IT operations at Fortune 500 enterprises.Lalit holds a Master’s degree in Engineering, and an MBA from UCLA.
Bio from: gartner-data-analytics-uk-2025
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