Download JNTUH MCA 5th Sem R17 2019 December 844AM Big Data Analytics Question Paper

Download JNTUH (Jawaharlal nehru technological university) MCA (Master of Computer Applications) 5th Sem (Fifth Semester) Regulation-R17 2019 December 844AM Big Data Analytics Previous Question Paper

R17

Code No: 844AM















JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

MCA V Semester Examinations, December - 2019

BIG DATA ANALYTICS

Time: 3hrs













Max.Marks:75

S

Note: This question paper contains two parts A and B.

Part A is compulsory which carries 25 marks. Answer all questions in Part A. Part B
consists of 5 Units. Answer any one full question from each unit. Each question carries
10 marks and may have a, b, c as sub questions.



PART - A



















5 ? 5 Marks = 25

1.a) List the types and sources of big data.











[5]

b) Differentiate between monetized analytics and operational analytics.



[5]

c) What points to be considered in designing a file to support Map Reduce implementation?






















[5]

d) What is NoSQL? Where is it used?











[5]

e) List the key elements of social media.











[5]



PART - B

5 ? 10 Marks = 50

2.

Describe three types of analytics and various analytical approaches typically associated
with big data.

















[10]

OR

3.a)

Explain the importance of parallel computing for big data.

b)

What are the key questions to be answered by all organizations stepping into analytics?

[5+5]

4.

Explain the differences between reporting and analysis with suitable example scenarios.

























[10]

OR

5.a)

Illustrate various phases of analysis process.

b)

Make a brief comparison of R and SAS tools.









[5+5]


6.

Discuss the role of HBase in big data processing with suitable examples.

[10]

OR

7.a)

Briefly discuss any five hadoop-specific file system types.

b)

What is the functionality of Hadoop YARN?









[5+5]


8.a)

Discuss the advantages of shared nothing architecture.

b)

List the components of the Hadoop ecosystem.









[5+5]

OR

9.

What are the limitations of relational database management system? Explain how hadoop
has overcome them.















[10]


10.a) What parameters are applied to classify the given text in the process of sentiment

analysis?

b) Discuss briefly online tools used to perform sentiment analysis.



[5+5]

OR

11.a) What is the importance of location-based tracking tools?
b) Differentiate between internal and external mobile analytics tools.



[5+5]



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