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AI-Driven Data Architectures for Real-Time Decision-Making in Enterprise Systems

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36

min

AI-Driven Data Architectures for Real-Time Decision-Making in Enterprise Systems

publish date

Mar 12, 2025

duration

36

min

Difficulty

Intermediate

Case details

In today’s business environment, the ability to make real-time, data-driven decisions has become a critical factor for maintaining competitive advantage. This presentation explores the integration of AI-driven data architectures within enterprise systems, focusing on building scalable data lakes and real-time data processing pipelines. Attendees will learn about best practices for designing AI-ready data architectures that accommodate large volumes of structured and unstructured data, support real-time analytics, and ensure data accessibility and integrity. Practical use cases and success stories will be discussed to illustrate how AI-enhanced data architectures can enable rapid insights and strategic decisions in dynamic business contexts.

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About Author

AI Technical Lead

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Artificial Intelligence

Denis Prilepskiy is a technology strategist and enterprise architecture expert with over 14 years of experience leading large-scale digital transformation projects across the UK, Middle East, and Eastern Europe. As a former Associate at McKinsey & Company, he has played a pivotal role in optimising IT organisations, securing multi-million dollar technology contracts, and implementing AI-driven enterprise solutions. His expertise spans enterprise architecture, IT infrastructure optimisation, and emerging technologies such as AI, blockchain, and IoT. With certifications in TOGAF, ITIL4, and FinOps, Denis has advised leading financial institutions, telecom giants, and global enterprises on modernising core systems, improving operational efficiency, and driving innovation. His insights into digital strategy and IT governance make him a sought-after speaker at technology and business conferences.

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