Case Study - Big Data Ingestion

The video tutorial discusses the role of Kafka in data ingestion, highlighting its dual function as a speed layer for real-time applications and a buffer for data ingestion into analytic stores. It explains a typical big data ingestion framework, where Kafka acts as a massive buffer, receiving data from various sources and feeding it into real-time analytics dashboards. The tutorial also covers the batch layer, where data is stored in systems like Hadoop, Amazon S3, or RDBMS for batch queries, data science, reporting, and long-term storage. The video concludes by formalizing these concepts.

What roles does Kafka serve in real-time applications?

Describe the typical components of a big data ingestion framework.

Explain the significance of using connectors to transfer data from Kafka to other systems.

How does Kafka function as a buffer in data ingestion?

What is the purpose of the batch layer in a big data architecture?