Course Title: Big Data Analysis
Course Code: PCC-CSE-404-G
Semester: B.Tech. 8th Semester (CSE)
May — 2024 Examination
Short Answer Questions [Compulsory]
- Answer the following:
(a) Enlist 5 challenges associated with managing and analyzing large volumes of data.
(b) Compare and contrast RDBMS and NoSQL.
(c) What are different types of data models and their applications in organizing and structuring large datasets?
(d) What do you mean by Big Data Processing pipeline?
(e) Briefly elaborate the six V of big data.
Unit-I [15 marks]
- Explain the characteristics of Big Data and discuss how they contribute to the challenges in managing large volumes of data. [15]
- (a) Describe the steps involved in the Data Science process. How does each step contribute to extracting value from Big Data? [8]
(b) Illustrate with a real-world scenario for steps involving Data Science process. [7]
Unit-II [15 marks]
- Compare and contrast Relational Database Management System (RDBMS) and NoSQL database in the context of Big Data storage and Management. Discuss the advantages and disadvantages of each approach. [15]
- (a) Explain the concept of Data lakes and how they are different from data marts. [8]
(b) Discuss the role of ETL (Extract, Transform, Load) processes and data pipelines in building and maintaining Data Lakes. [7]
Unit-III [15 marks]
- Explain the concept of scalability in the context of Big Data storage and management systems. Discuss the scalability challenges associated with traditional DBMS and how they differ from those of Big Data Management System. [15]
- Discuss the importance of data quality in Big Data Management. What are the key challenges in ensuring data quality at scale? How can organizations address these challenges effectively? [15]
Unit-IV [15 marks]
- Describe the key components of Big Data processing pipelines. How do these components work together to ingest, process, and analyze large volumes of data? [15]
- Write short notes on:
(a) Hadoop
(b) Cassandra [15]
May — 2023 Examination
Short Answer Questions [Compulsory]
- Write short note on the following:
(i) Data Sciences
(ii) ELT
(iii) Sources of data using service bindings
(iv) Data ingestion
(v) MongoDB
(vi) DFS
Unit-I [15 marks]
- (a) What is Big Data? Explain various characteristics, challenges and applications of Big Data.
(b) What is HDFS? Explain its components. [15] - (a) Explain six V's of Big Data in detail.
(b) Write short note on foundation for big data system. [15]
Unit-II [15 marks]
- (a) Define Data Mart. Explain different types of data marts with example. Also discuss advantages and disadvantages of data marts.
(b) Explain RDBMS features and architecture in detail. [15] - (a) What is NoSQL? Explain different types of NoSQL databases with example. Differentiate SQL and NoSQL with example.
(b) Write short note on different types of file formats used in big data. [15]
Unit-III [15 marks]
- What is Modeling? Explain various types of data models with example. [15]
- (a) Explain different types of big data management techniques.
(b) Write short note on real life applications of big data. [15]
Unit-IV [15 marks]
- (a) What is Hive? Explain Hive features, Hive integration and workflow and architecture in detail.
(b) Write short note on Hive Query Language (HQL). [15] - (a) Write short note on Pig architecture and commands.
(b) Explain MapReduce working. WAP for Word Count using MapReduce. [15]
July — 2022 Examination
Short Answer Questions [Compulsory]
- Explain the following:
(a) Big Data
(b) Map Reduce
(c) YARN
(d) Data Mart
(e) ETL
(f) Six V in big data
Section-A [15 marks]
- Define the different techniques in big data analytics. [15]
- Discuss the following in detail:
(i) Challenges in big data
(ii) Types of Data [15]
Section-B [15 marks]
- What is Big Data Platform? Describe the main features of a big data platform in detail. [15]
- Define HDFS. Describe name node, data node and block. Explain HDFS operations in detail. [15]
Section-C [15 marks]
- (i) Compare Traditional Data and Big Data.
(ii) Describe any five real life applications of Big Data. [15] - What is Real Time Analytics? Discuss their technologies in detail. [15]
Section-D [15 marks]
- (i) What is Hadoop? Explain its components.
(ii) How do you analyze the data in Hadoop? [15] - What is Real-Time Analytics? Discuss their technologies in detail. [15]