Data Processing Big Data Processing 2

Question 1

What is stream processing in big data?

Accepted Answer

Continuously processing data as it arrives in real time

Answer

Stream processing handles data continuously as it is generated, enabling real-time analysis and immediate actions on incoming data.

Question 2

What is Apache Kafka primarily used for?

Accepted Answer

Distributed real-time data streaming and messaging

Answer

Apache Kafka is a distributed event-streaming platform used for high-throughput, fault-tolerant messaging and real-time data pipeline construction.

Question 3

What distinguishes batch processing from stream processing?

Accepted Answer

Batch processing handles data in large collected groups at scheduled intervals; stream processing handles data continuously as it arrives

Answer

Batch processing accumulates data over a period and processes it all at once on a schedule, while stream processing ingests and analyzes data continuously in near-real-time.

Question 4

What is a data warehouse?

Accepted Answer

A centralized repository of integrated, structured data optimized for reporting and analysis

Answer

A data warehouse is a subject-oriented, integrated, time-variant, and non-volatile collection of data designed to support business intelligence and decision-making.

Question 5

What is horizontal scaling in the context of big data systems?

Accepted Answer

Adding more machines to a cluster to increase processing capacity

Answer

Horizontal scaling (scale-out) adds more nodes to a distributed system to increase capacity, as opposed to vertical scaling which upgrades a single machine.

Data Processing Practice Test

Data Processing Practice Test

Data Processing Big Data Processing 2