Big Data Concept

  Introduction In today’s data-driven world, organizations face the challenge of extracting actionable insights from massive datasets to drive informed decision-making. H2O.ai, a leading open-source machine learning and artificial intelligence platform, addresses this challenge by providing scalable, efficient, and accessible tools for predictive analytics. With its ability to process big data, automate complex machine learning workflows, and integrate seamlessly with enterprise systems, H2O.ai has become a cornerstone for businesses across industries like finance, healthcare, retail, and telecommunications. This chapter explores H2O.ai’s architecture, key features, use cases, and its role in democratizing AI for big data predictive analytics. What is H2O.ai? H2O.ai is an open-source, distributed, in-memory machine learning platform designed to handle large-scale data processing and predictive analytics. Launched in 2012, H2O.ai has evolved into a robust ecosystem that empowers ...

  Introduction In the rapidly evolving landscape of artificial intelligence (AI), the emergence of agentic AI represents a paradigm shift from passive tools to proactive entities capable of independent action. Agentic AI systems, often referred to as AI agents, are designed to perceive their environment, reason about goals, plan sequences of actions, and execute them autonomously. This chapter delves into the integration of agentic AI within data-driven enterprises—organizations that leverage vast amounts of data to inform strategy, operations, and innovation. As businesses increasingly rely on data analytics, machine learning, and real-time insights, agentic AI offers a pathway to autonomous decision-making, enabling enterprises to operate with unprecedented efficiency, agility, and intelligence. The chapter explores the foundational concepts of agentic AI, its synergy with data-driven frameworks, practical applications, benefits, challenges, and future implications. By exami...