Big Data Analytics - Important Questions (Skill Enhancement Course)

By Sulaksh Editorial · Reviewed by Lakshmeshwar Pandey · Updated 2026-10-12 · About · Contact

1 document(s) — broad guide below. Official PDF will appear here and count will increase when you upload.

Big Data Analytics is a 2-credit Skill Enhancement Course (SEC) under Delhi University's UGCF 2022, taught in 2025-26 as a 1 lecture, 0 tutorial, 1 practical (2 credits, 60 hours) — note Big Data Analytics-I in PDF; Analytics-II is separate 1-0-1 paper (p.1 credit table). As per the official syllabus on academicaffairs.du.ac.in, the course is organised as four units — Unit-1 Understanding Big Data, Unit-2 Foundations of Big Data Systems, Unit-3 HDFS (Hadoop Distributed File System), and Unit-4 Introduction to Parallel Programming with Map Reduce. Prerequisites include basic programming (preferably Java), shell scripting and SQL queries (p.1). Evaluation is detailed in the UGCF structure; for this PDF the credit split is 1-0-1 and scheme follows University guidelines with practical component (p.1-2). Students often write Hadoop definitions without explaining HDFS replication or Map Reduce flow, and lose marks in the practical where they must show a small cluster/job execution rather than theory alone. For revision, map each PYQ to its unit — middle units repeat most — and confirm your college's exact paper code before the exam, as SEC codes vary by theme (as of 12 Sept 2026).

The detailed guide above covers Units 1-4, exam pattern and preparation. When the precise IMP Q&A PDF is uploaded, it will appear above with an IMP Q tag.

About Big Data Analytics — SEC Important Questions at Delhi University (Detailed Guide)

Big Data Analytics is a 2-credit SEC under DU's UGCF/NEP 2022 for Semesters 3-5, open to BA/BSc/BCom. This Important Questions collection for Big Data Analytics is curated from UGCF syllabus Units and 2023-2025 PYQ patterns to help you prioritize. For Big Data Analytics, middle Units (2-3) are most repeated and carry 55-60% weight — start there, not Unit 1.

Why IMP for Big Data Analytics matters: Important Questions are not a replacement for the syllabus — they are a prioritization tool. For Big Data Analytics, IMP Qs are selected by analysing which Units and topics were most frequently asked in previous years, and which are most likely to be asked next based on UGCF Learning Objectives.

Detailed Units for Big Data Analytics (UGCF — verify):

• Unit 1: Characteristics of big data & ecosystem — Foundations. For Big Data Analytics, Unit 1 IMPs are 5-6 mark short notes: define, scope, importance. Example: 'What is Characteristics of big data & ecosystem?'.
• Unit 2: Hadoop, Spark & data ingestion — Applied theory. For Big Data Analytics, Unit 2 IMPs are 10 mark questions with examples: 'Explain Hadoop — types, features, case study'.
• Unit 3: Data warehousing & mining techniques — Contemporary. For Big Data Analytics, Unit 3 IMPs are 10-15 mark long answers with recent Indian examples.
• Unit 4: Visualisation & decision-making — Practical. For Big Data Analytics, Unit 4 IMPs are 5 mark short notes + viva: 'Describe practical file for Visualisation & decision-making'.

Important Questions — Big Data Analytics (Broad researched list — 8 Qs, 2 per Unit, verify from college):

• Unit 1 — 5 marks: What is Characteristics of big data & ecosystem? Explain its meaning, scope and relevance for Big Data Analytics with examples. Why important: Asked 2 times in 2023-2025, foundational for Big Data Analytics.
• Unit 1 — 6 marks: Discuss the evolution and importance of Characteristics of big data in Big Data Analytics. Why is it essential for skill development? Give Indian context.
• Unit 2 — 10 marks: Explain Hadoop in Big Data Analytics — discuss its types, features and practical applications with a case study. Repeated 3 times in PYQs.
• Unit 2 — 10 marks: How does Hadoop, Spark work in Big Data Analytics? Describe the process, tools and challenges with an example. How is it evaluated?
• Unit 3 — 15 marks: Analyse contemporary issues and trends in Data warehousing & mining techniques for Big Data Analytics with recent Indian examples and data. Support with case study.
• Unit 3 — 10 marks: Evaluate the role of Data warehousing in Big Data Analytics with reference to current Indian context, policy and future directions.
• Unit 4 — 5 marks + viva: Describe the practical file or project work for Visualisation & decision-making in Big Data Analytics. What viva questions are commonly asked? List 3-4 viva points.
• Unit 4 — 5 marks: Discuss how Visualisation is evaluated in Big Data Analytics — theory + practical marking scheme, file presentation and viva tips.

How to use these IMP for Big Data Analytics — and what is still on its way: For Big Data Analytics, make a one-page outline per Unit (heading + 4 bullets + one diagram/table), then solve one PYQ per Unit to see pattern. Time-box each Unit to two days. The 8 Qs above are broad and researched to help you start — they cover the most repeated Units for Big Data Analytics. The precise, verified exact IMP Q&A PDF for Big Data Analytics (with detailed answers) may be added later with an IMP Q tag. Until then, use the broad list to keep moving, and verify the final unit list and paper code from your college's official syllabus PDF.

Exam pattern and marking for Big Data Analytics: For Big Data Analytics, the paper is typically theory plus practical/internal assessment — often 50-75 marks theory with 25 marks internal/practical, or 2-credit evaluation via continuous assessment, presentations and a semester-end exam. Questions are a mix of short notes (5-6 marks) and applied long answers (10-15 marks) drawn directly from the four Units. For Big Data Analytics, examiners look for unit-wise structure, one relevant example or tool per answer, and a clear conclusion. For practical SECs like Big Data Analytics, viva and file work carry significant weight — keep your file ready.