Why streaming enables real-time analytics in Apache Spark - Quick Recap

Recall & Review

beginner

What is streaming in data processing?

Streaming is a method of continuously processing data as it arrives, rather than waiting for all data to be collected first.

beginner

How does streaming enable real-time analytics?

Streaming allows data to be analyzed immediately as it comes in, so insights and decisions can be made without delay.

beginner

What is a key difference between batch processing and streaming?

Batch processing waits for all data to be collected before analysis, while streaming processes data continuously as it arrives.

intermediate

Why is low latency important in streaming analytics?

Low latency means data is processed quickly after arrival, enabling fast responses and timely decisions.

beginner

Name one real-life example where streaming analytics is useful.

Monitoring traffic in a city to adjust signals in real-time or detecting fraud in financial transactions instantly.

What does streaming data processing do?

A Deletes data after collection

B Waits for all data before processing

C Processes data continuously as it arrives

D Stores data without analysis

Streaming processes data continuously, enabling real-time analytics.

Which is a benefit of streaming analytics?

A Delayed insights

B Batch data storage

C Data loss

D Real-time decision making

Streaming analytics allows decisions to be made in real-time.

What is latency in streaming analytics?

A Speed of data deletion

B Time delay between data arrival and processing

C Amount of data stored

D Size of data batch

Latency is the delay between when data arrives and when it is processed.

Which scenario best uses streaming analytics?

A Real-time fraud detection

B Archiving old data

C Yearly tax filing

D Monthly sales report

Real-time fraud detection requires immediate data processing, ideal for streaming.

What is the main difference between batch and streaming?

A Batch processes data after collection, streaming processes continuously

B Streaming waits for all data

C Batch processes data continuously

D Streaming deletes data

Batch waits for all data before processing; streaming processes data as it arrives.

Explain how streaming enables real-time analytics and why it matters.

Think about how data arrives and is analyzed without waiting.

Describe a real-world example where streaming analytics improves outcomes.

Consider situations needing instant action based on data.