In the ECET 2026 exam for CSE diploma students, the topic Big Data is one of the most modern and emerging areas in Computer Science. It is part of the C-23 curriculum and is gaining high importance in technology-driven subjects like Data Science, AI, and Analytics. Understanding Big Data basics can help you score easy MCQs and also prepare you for future industry trends. Let’s explore the core concept of Big Data, its features, and solve 10 targeted MCQs with answers and explanations.
📘 Concept Notes – Big Data Introduction
📚 What is Big Data?
Big Data refers to extremely large datasets that cannot be handled using traditional database systems. These datasets are generated at high speed, come in varied formats, and require advanced tools and technologies to process, analyze, and visualize.
📦 The 5 Vs of Big Data:
- Volume – Huge amount of data generated every second (e.g., social media, sensors).
- Velocity – Speed at which data is generated and processed.
- Variety – Data comes in various formats: text, audio, video, images, logs.
- Veracity – Refers to data accuracy, noise, and inconsistencies.
- Value – The insights or benefits derived from analyzing Big Data.
🛠 Big Data Technologies & Tools:
- Hadoop – Framework for distributed data processing.
- MapReduce – Programming model for parallel data computation.
- Spark – Fast, in-memory data processing engine.
- NoSQL Databases – MongoDB, Cassandra (for unstructured data).
- Data Lakes – Repositories that store data in its raw format.
🌍 Real-Life Applications of Big Data:
- Recommender Systems (Netflix, Amazon)
- Traffic and GPS tracking
- Fraud detection in banking
- Predictive analytics in healthcare
- Sentiment analysis on social media
🔟 10 Most Expected MCQs – ECET 2026 [Big Data – Introduction]
Q1. What is the main characteristic that defines Big Data?
A) Large processing power
B) High bandwidth
C) Large data sets
D) Long backup time
Q2. Which of the following is NOT a V of Big Data?
A) Volume
B) Visibility
C) Velocity
D) Variety
Q3. Hadoop is a framework for:
A) Network programming
B) Image processing
C) Distributed data processing
D) Web development
Q4. Which tool is designed for in-memory Big Data processing?
A) MapReduce
B) Spark
C) MongoDB
D) Excel
Q5. Which of the following is a NoSQL database used in Big Data?
A) Oracle
B) SQL Server
C) MongoDB
D) MS Access
Q6. The term ‘Variety’ in Big Data refers to:
A) Data size
B) Data speed
C) Data formats
D) Data types only in SQL
Q7. Sentiment analysis on tweets is an example of:
A) Real-time computation
B) Traditional analytics
C) Static file reading
D) Manual processing
Q8. What does Veracity in Big Data refer to?
A) Speed of data
B) Trustworthiness of data
C) Storage of data
D) Format of data
Q9. Which of the following is an open-source Big Data framework?
A) MS Excel
B) Oracle
C) Hadoop
D) Notepad++
Q10. The main benefit of Big Data is to extract:
A) Backup logs
B) System commands
C) Useful insights
D) UI designs
✅ Answer Key Table
| Q.No | Answer |
|---|---|
| Q1 | C |
| Q2 | B |
| Q3 | C |
| Q4 | B |
| Q5 | C |
| Q6 | C |
| Q7 | A |
| Q8 | B |
| Q9 | C |
| Q10 | C |
🧠 Explanations of All Answers
- Q1 → C: Big Data deals with very large datasets.
- Q2 → B: Visibility is not one of the 5 Vs; correct one is Veracity.
- Q3 → C: Hadoop is used for distributed storage and data processing.
- Q4 → B: Spark is known for fast in-memory data processing.
- Q5 → C: MongoDB is a NoSQL database suitable for Big Data.
- Q6 → C: Variety relates to different data formats like video, text, logs, etc.
- Q7 → A: Sentiment analysis often needs real-time processing of data streams.
- Q8 → B: Veracity is about the quality and reliability of data.
- Q9 → C: Hadoop is a well-known open-source Big Data framework.
- Q10 → C: The primary goal of Big Data is to extract useful business insights.
🎯 Why This Practice Matters for ECET 2026
Big Data is a hot topic in the tech world, and its basic concepts are frequently asked in ECET CSE papers. This is one of the easiest theory-based scoring areas. If you revise these MCQs, you’re likely to get 1–2 marks easily with minimal effort. Plus, understanding Big Data basics gives you a head start for future B.Tech-level projects in AI and data science.
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