Big Data is a broad term referring to large, complex datasets that are difficult to manage and analyze using traditional tools. Hadoop is an open-source framework that provides solutions for storing and processing Big Data. Hadoop is designed to handle large volumes of data and can store different types of data, including structured, unstructured, and semi-structured data.

Elaboration:

• Big Data : Refers to the vast amount of data generated by various sources, often characterized by its volume, velocity, variety, veracity, and value
• Hadoop : Is a framework that uses distributed storage (HDFS) and parallel processing (MapReduce) to handle and process Big Data efficiently
• Hadoop's Role : Hadoop helps organizations manage and analyze large datasets by distributing the data across a cluster of machines and processing it in parallel.
• Benefits of Hadoop :Hadoop offers several advantages, including cost-effectiveness, high performance, fault tolerance, and scalability, making it a suitable choice for handling Big Data workloads

Hadoop's Components:

• HDFS (Hadoop Distributed File System) : Stores data across multiple machines in a distributed manner.
• MapReduce : A programming model for parallel processing of data
• YARN (Yet Another Resource Negotiator) : Manages resources and assigns tasks across the cluster.

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