Big Data: Processing and Management

This lecture covers the challenges of handling large data volumes, discussing the growth of digital data, the characteristics of big data (volume, velocity, variety, variability, veracity), and the Gamma Parallel Database Machine. It also explores declustering techniques like Hash and Range, their tradeoffs, and failure management strategies such as Interleaved and Chained Declustering. The lecture delves into the details of how data is spread across nodes, the impact of failure on data availability, and the process of recovering data in case of node failures.