Data Processing Data Processing Tools and Technologies

Question 1

What is Apache Spark primarily used for?

Accepted Answer

Fast, distributed large-scale data processing in memory across a cluster

Answer

Apache Spark is an open-source distributed processing engine that performs in-memory batch and stream processing up to 100x faster than Hadoop MapReduce.

Question 2

What is Apache Kafka primarily used for?

Accepted Answer

High-throughput distributed event streaming and message queuing

Answer

Apache Kafka is a distributed event streaming platform that handles millions of events per second for real-time data pipelines and stream processing.

Question 3

What does a message broker do in a data pipeline?

Accepted Answer

Routes and queues messages between producers and consumers to decouple systems

Answer

A message broker receives messages from producers and routes them to the appropriate consumers, decoupling senders and receivers so they don't depend on each other directly.

Question 4

What is dbt (data build tool) used for in data engineering?

Accepted Answer

Transforming data inside a warehouse using SQL-based models and version-controlled code

Answer

dbt enables data analysts and engineers to write SQL transformations as versioned, tested, documented models that run directly inside the data warehouse.

Question 5

What is Snowflake in the context of data processing?

Accepted Answer

A cloud-native data warehouse platform that separates compute and storage

Answer

Snowflake is a cloud-native data warehouse that decouples compute from storage, allowing independent scaling and supporting multiple concurrent workloads.

Data Processing Practice Test

Data Processing Practice Test

Data Processing Data Processing Tools and Technologies