Big Data refers to exceptionally large and complex datasets that exceed the capabilities of traditional data management tools, characterized by the "5 V's": Volume, Variety, Velocity, Veracity, and Value. These datasets, spanning structured, semi-structured, and unstructured formats, are crucial in diverse fields such as healthcare, finance, telecommunications, transportation, and IoT, enabling advanced analytics and data-driven decision-making. Key challenges in managing Big Data include storage scalability, data ingestion, processing frameworks, security, and data quality management, with technologies like Apache Kafka, Hadoop, and Spark playing vital roles. Cloud platforms like AWS, Google Cloud, and Azure have further enhanced Big Data engineering by offering scalable, on-demand infrastructure, while best practices emphasize scalability planning, process automation, data governance, and continuous monitoring. Tools like PubNub facilitate real-time data ingestion, event streaming, and analytics, supporting Big Data technologies such as Apache Kafka and Spark, and enhancing applications in gaming, stock trading, and smart city development.