1. Introduction to Big Data In today’s digital world, data is being generated at an unprecedented rate. Every second, millions of searches, transactions, tweets, sensor readings, and video uploads occur. This massive amount of data, which traditional database systems cannot handle efficiently, is known as Big Data .
| Era | Characteristics | |------|----------------| | | Relational databases (RDBMS) – structured data, small scale. | | 1990s | Data warehouses – aggregated data for business intelligence. | | 2000s | Internet boom – unstructured data from web logs, emails, social media. | | 2010s onwards | Big Data technologies (Hadoop, Spark, NoSQL) – handle petabytes of data. | what is big data - javatpoint
Big Data refers to extremely large and complex datasets that require advanced tools, techniques, and architectures to store, process, and analyze them for valuable insights. Big Data is a collection of data that is huge in volume, growing exponentially with time, and is so complex that it cannot be processed by conventional data processing systems like relational databases (RDBMS). 2. The Evolution of Big Data To understand Big Data, we must look at how data management evolved: This massive amount of data, which traditional database