Exam Details
| Subject | big data | |
| Paper | ||
| Exam / Course | mca(integrated) | |
| Department | ||
| Organization | Gujarat Technological University | |
| Position | ||
| Exam Date | May, 2017 | |
| City, State | gujarat, ahmedabad |
Question Paper
1
Seat No.: Enrolment
GUJARAT TECHNOLOGICAL UNIVERSITY
MCA Integrated SEMESTER- VIII • EXAMINATION SUMMER 2017
Subject Code:4480601 Date: 27/04/2017
Subject Name: BIG DATA
Time: 10:30 am to 1:00 pm Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1
Define the terms: "BI", "NoSQL", and "cluster".
ii) Compare the terms "data analysis" and "data analytics" in brief.
iii) Compare the terms "file system" and distributed file system".
03
02
02
Describe CAP theorem along with appropriate example.
07
Q.2
Define Big Data and state its characteristics. Why do we need Big Data analysis? Explain.
07
State the developments in ICT that have acted as catalysts towards adoption of Big Data in businesses and explain each of them in brief.
07
OR
State the stages of Big Data analytics lifecycle.
ii) State the difference between traditional data visualization and data visualization for Big Data.
04
03
Q.3
State various categories of NoSQL databases and explain each of them in brief.
07
Describe eventually consistent non-relational databases in detail.
07
OR
Q.3
What is HBase? Explain how data is stored in HBase using appropriate example.
07
What do you mean by the term "horizontal scaling"? Describe how horizontal scaling is achieved in MongoDB.
07
Q.4
What is MapReduce? Explain various map tasks of MapReduce with appropriate example.
07
Explain the terms parallel data processing and distributed data processing.
ii) State and describe the types of workloads that are processed in Big Data.
03
04
OR
Q.4
Describe the concepts "task parallelism" and "data parallelism" along with appropriate example. Which of these concepts is adopted by MapReduce?
07
Explain the reason why MapReduce is not considered suitable for real-time data processing and how it can be enabled to work in a near-real-time scenario.
07
Q.5
Mention the types of data analysis and explain each of them in brief.
07
State the techniques of machine learning and explain each of them in brief.
07
OR
Q.5
Explain the terms "quantitative analysis" and "qualitative analysis".
ii) Compare the terms correlation and regression. How are they used in Big Data analytics? Explain.
03
04
Explain how group operation is performed while querying data in MongoDB.
ii) Compare mongodump and mongoexport utilities in brief.
04
03
Seat No.: Enrolment
GUJARAT TECHNOLOGICAL UNIVERSITY
MCA Integrated SEMESTER- VIII • EXAMINATION SUMMER 2017
Subject Code:4480601 Date: 27/04/2017
Subject Name: BIG DATA
Time: 10:30 am to 1:00 pm Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1
Define the terms: "BI", "NoSQL", and "cluster".
ii) Compare the terms "data analysis" and "data analytics" in brief.
iii) Compare the terms "file system" and distributed file system".
03
02
02
Describe CAP theorem along with appropriate example.
07
Q.2
Define Big Data and state its characteristics. Why do we need Big Data analysis? Explain.
07
State the developments in ICT that have acted as catalysts towards adoption of Big Data in businesses and explain each of them in brief.
07
OR
State the stages of Big Data analytics lifecycle.
ii) State the difference between traditional data visualization and data visualization for Big Data.
04
03
Q.3
State various categories of NoSQL databases and explain each of them in brief.
07
Describe eventually consistent non-relational databases in detail.
07
OR
Q.3
What is HBase? Explain how data is stored in HBase using appropriate example.
07
What do you mean by the term "horizontal scaling"? Describe how horizontal scaling is achieved in MongoDB.
07
Q.4
What is MapReduce? Explain various map tasks of MapReduce with appropriate example.
07
Explain the terms parallel data processing and distributed data processing.
ii) State and describe the types of workloads that are processed in Big Data.
03
04
OR
Q.4
Describe the concepts "task parallelism" and "data parallelism" along with appropriate example. Which of these concepts is adopted by MapReduce?
07
Explain the reason why MapReduce is not considered suitable for real-time data processing and how it can be enabled to work in a near-real-time scenario.
07
Q.5
Mention the types of data analysis and explain each of them in brief.
07
State the techniques of machine learning and explain each of them in brief.
07
OR
Q.5
Explain the terms "quantitative analysis" and "qualitative analysis".
ii) Compare the terms correlation and regression. How are they used in Big Data analytics? Explain.
03
04
Explain how group operation is performed while querying data in MongoDB.
ii) Compare mongodump and mongoexport utilities in brief.
04
03
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