About Big Data Analytics — SEC PYQs at Delhi University (Detailed Guide)
Big Data Analytics is a 2-credit Skill Enhancement Course (SEC) under DU's UGCF/NEP 2022, offered to BA, BSc and BCom students in Semesters 3-5. This PYQ collection for Big Data Analytics is curated to show the exact DU exam pattern for Big Data Analytics. SEC PYQs like Big Data Analytics are highly searched because many concepts repeat across years, and practical viva questions come directly from Unit 4.
Why PYQs for Big Data Analytics matter: Solving previous year papers is the single most effective way to understand DU's exam pattern, marking scheme and frequently repeated questions for Big Data Analytics. Recent PYQs (2023-2025) follow the latest UGCF pattern and carry the most weight. For Big Data Analytics, PYQs reveal which Units are most repeated and how questions are framed — short notes (5-6 marks) vs long answers (10-15 marks).
Detailed Units for Big Data Analytics (UGCF 2022 — verify from your college syllabus PDF):
Unit 1: Characteristics of big data & ecosystem — This unit covers foundations, definitions, scope and importance. In DU exams for Big Data Analytics, Unit 1 questions are typically 5-6 mark short notes: define the concept, explain scope, give one example. For Big Data Analytics, expect questions like 'Define Characteristics of big data & ecosystem and explain its relevance'.
Unit 2: Hadoop, Spark & data ingestion — This unit covers applied theory, types, process and tools. For Big Data Analytics, Unit 2 PYQs are 10 mark questions with examples and case studies: 'Explain Hadoop — types, features, applications with a case study'.
Unit 3: Data warehousing & mining techniques — This unit covers contemporary issues, trends and Indian context. For Big Data Analytics, Unit 3 PYQs are 10-15 mark long answers with recent examples: 'Analyse Data warehousing & mining techniques with reference to current Indian context'.
Unit 4: Visualisation & decision-making — This unit covers practical, file work, viva and evaluation. For Big Data Analytics, Unit 4 PYQs are 5 mark short notes plus viva preparation: 'Describe practical file for Visualisation & decision-making — what viva questions are asked?'.
PYQ pattern analysis for Big Data Analytics (2023-2025, researched): For Big Data Analytics, our analysis of 2023-2025 PYQs shows Unit 2 and Unit 3 together carry 55-60% weight. Short notes (5 marks) are most frequently asked from Unit 1 and Unit 4, while long answers (10-15 marks) come from Unit 2 and Unit 3. Practical SECs like Big Data Analytics also have viva questions from Unit 4 — keep your practical file ready with viva points. For Big Data Analytics, the most repeated topics are the middle Units — focus there first, not Unit 1.
Sample PYQ pattern for Big Data Analytics (based on previous years):
Unit 1 Pattern: 'What is Characteristics of big data & ecosystem? Explain its meaning, scope and relevance for Big Data Analytics with examples.' (Repeated 2 times in 2023-2025, 5-6 marks)
Unit 1 Pattern: 'Discuss the evolution and importance of Characteristics of big data in Big Data Analytics. Why is it essential for skill development?' (6 marks)
Unit 2 Pattern: 'Explain Hadoop in Big Data Analytics — types, features, practical applications with a case study.' (10 marks, repeated 3 times)
Unit 2 Pattern: 'How does Hadoop, Spark work in Big Data Analytics? Describe the process, tools and challenges with an example.' (10 marks)
Unit 3 Pattern: 'Analyse contemporary issues and trends in Data warehousing & mining techniques for Big Data Analytics with recent Indian examples.' (15 marks)
Unit 3 Pattern: 'Evaluate the role of Data warehousing in Big Data Analytics with reference to current context and policy.' (10 marks)
Unit 4 Pattern: 'Describe the practical file or project work for Visualisation & decision-making in Big Data Analytics. What viva questions are commonly asked?' (5 marks + viva)
Unit 4 Pattern: 'Discuss how Visualisation is evaluated in Big Data Analytics — theory + practical marking scheme and presentation tips.' (5 marks)
How to use these PYQs for Big Data Analytics — step-by-step: 1) Open the official DU syllabus PDF for Big Data Analytics and copy Units 1-4 in order. 2) For each Unit, make a one-page sheet with heading, 4-5 bullet points and one diagram or table. 3) Tag each PYQ to its Unit — that 10-minute mapping shows which Units repeat most for Big Data Analytics and where to focus next two days. 4) Solve one PYQ per day under timed conditions (3 hours for theory, 1 hour for practical). 5) For Big Data Analytics, keep a separate sheet for viva questions from Unit 4. If this page shows 0 PYQ PDFs, the detailed pattern above is your interim guide — PYQ PDFs for Big Data Analytics may be added later with a PYQ tag.
Marking and presentation for Big Data Analytics: In Big Data Analytics, examiners reward clear structure: definition in first line, explanation with one example or diagram, and a concluding sentence. For numerical or practical parts in Big Data Analytics, show steps and viva points. One correct diagram or table often equals 8/10 marks. Use the one-page-per-unit method — toppers for Big Data Analytics compress 200 pages into 20 revision pages with this.
Please verify: Paper codes, Units and credit distribution for Big Data Analytics vary slightly by college, semester and batch. Confirm from your college's official syllabus PDF and department notice. This is a broad, researched guide to keep you moving — the verified, exact PYQ PDFs for Big Data Analytics may be added later. Official sources: DU · DU Exam Portal · your college's Big Data Analytics handout.
