Big Data Concept

  Introduction In the vast landscape of big data, the journey of data from its origin to actionable insights begins with ingestion and integration. Data ingestion refers to the process of collecting, importing, and processing data from various sources into a centralized system or ecosystem where it can be stored, analyzed, and utilized. This chapter explores how data enters the big data ecosystem from diverse sources, bridging the gap between raw data origins and analytical processes. The purpose of this phase is critical: it ensures that data from disparate, often heterogeneous sources is seamlessly funneled into storage systems like data lakes, warehouses, or processing engines, enabling downstream activities such as analytics, machine learning, and business intelligence. Big data environments deal with the "3 Vs" – volume, velocity, and variety – which amplify the complexity of ingestion. Volume demands scalable tools to handle petabytes of data; velocity requires rea...