Big Data Concept

  Introduction In today’s digital economy, organizations generate and store data from countless sources: enterprise applications, IoT devices, cloud services, customer interactions, and third-party systems. This data, often vast and heterogeneous, needs to be integrated before it can drive insights. Traditional approaches to data integration—manual ETL (Extract, Transform, Load) processes, rule-based pipelines, and custom scripts—are time-intensive, error-prone, and lack adaptability. Agentic AI , a new paradigm of autonomous and proactive artificial intelligence, is transforming this landscape. By automating integration processes, Agentic AI reduces human intervention, ensures data consistency, and enables real-time decision-making in big data platforms. Challenges in Traditional Data Integration Complexity of Sources – Data comes in structured, semi-structured, and unstructured formats. Scalability Issues – Manual pipelines often fail to handle petabyte-scale work...