Day 41 – Night Session: Big Data – Real-time Applications – ECET 2026

In ECET 2026 CSE, Big Data questions are not just about Hadoop but also about real-time applications. Knowing where Big Data is applied gives students confidence and helps in theory + application-based questions.

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📘 Concept Notes

🌐 What is Real-time Big Data?

• Real-time Big Data refers to processing and analyzing data as soon as it is generated.
• Involves tools like Apache Kafka, Spark Streaming, Flink.
• Useful when immediate decisions are required (fraud detection, alerts, monitoring).

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⚙️ Characteristics

1. Velocity: Fast data generation and processing.
2. Low Latency: Immediate insights with minimal delay.
3. Scalable: Handles millions of events per second.
4. Continuous Flow: Works on streaming data rather than static datasets.

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🔋 Formula – Real-time Throughput

If:

• Number of records =
• Time taken =

Then throughput is:

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📐 Example

If records processed in seconds,

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🛠 Real-time Applications of Big Data

1. Finance:
   • Fraud detection in credit card transactions.
   • Stock market analysis.
2. Healthcare:
   • Monitoring patients’ vitals in real-time.
   • Predicting emergencies with streaming data.
3. E-commerce:
   • Real-time product recommendations.
   • Cart abandonment detection.
4. Transportation:
   • Live traffic monitoring (Google Maps, Uber).
   • Predictive maintenance of vehicles.
5. Social Media & Communication:
   • Twitter trends analysis.
   • Spam detection in WhatsApp/Emails.
6. IoT (Internet of Things):
   • Smart homes and smart city monitoring.
   • Sensor data analysis.

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🔟 10 Expected MCQs – ECET 2026

Q1. Real-time Big Data means:
A) Processing data after storage
B) Processing data instantly as it arrives
C) Only batch processing
D) None

Q2. Throughput formula is:
A)
B)
C)
D)

Q3. A common tool for real-time streaming is:
A) Apache Pig
B) Apache Kafka
C) Hadoop HDFS
D) MapReduce

Q4. Real-time Big Data is mainly about:
A) High latency processing
B) Streaming data analysis
C) Static dataset storage
D) File system replication

Q5. If records are processed in seconds, throughput = ?
A) 500
B) 1000
C) 2500
D) 5000

Q6. An example of real-time Big Data in healthcare is:
A) Patient vital sign monitoring
B) Storing old lab reports
C) Database indexing
D) File compression

Q7. Which is NOT a real-time Big Data application?
A) Fraud detection
B) Stock market analysis
C) Weather prediction after 5 years
D) Live traffic analysis

Q8. Apache Spark Streaming is used for:
A) Batch processing only
B) Real-time stream processing
C) File storage
D) Metadata management

Q9. Real-time Big Data requires:
A) Low latency
B) High latency
C) No scalability
D) Static datasets

Q10. IoT data analysis in smart homes is an example of:
A) Batch processing
B) Real-time Big Data application
C) Static storage
D) Replication

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✅ Answer Key

Q.No	Answer
Q1	B
Q2	C
Q3	B
Q4	B
Q5	B
Q6	A
Q7	C
Q8	B
Q9	A
Q10	B

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🧠 Explanations

• Q1 → B: Real-time means immediate processing.
• Q2 → C: Throughput = .
• Q3 → B: Apache Kafka = streaming tool.
• Q4 → B: Streaming analysis is key.
• Q5 → B: .
• Q6 → A: Real-time patient monitoring.
• Q7 → C: Weather prediction is not real-time.
• Q8 → B: Spark Streaming = real-time.
• Q9 → A: Low latency is required.
• Q10 → B: IoT devices generate continuous data streams.

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🎯 Why Practice Matters

• Real-time applications are often asked in theory-based questions.
• Formula-based throughput problems can fetch direct marks.
• Helps in practical understanding of Big Data use in industries.

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