Download JNTUH MCA 4th Sem R15 2018 June-July 824AM Big Data Analytics Question Paper

Download JNTUH (Jawaharlal nehru technological university) MCA (Master of Computer Applications) 4th Sem (Fourth Semester) Regulation-R15 2018 June-July 824AM Big Data Analytics Previous Question Paper

R15

Code No: 824AM















JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

MCA IV Semester Examinations, June/July - 2018

BIG DATA ANALYTICS

Time: 3hrs













Max.Marks:75


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) What are the challenges with big data?











[5]

b) What is the difference between reporting and analysis?







[5]

c) Make a comparison of RDBMS and HBase.









[5]

d) What are the challenges faced by distributed computing?





[5]



e) Compare web analytics with social media analytics.







[5]



PART - B

















5 ? 10 Marks = 50


2.

What is big data analytics? Discuss various applications of big data analytics.

[10]

OR

3.

What traits need to be honed by a technical professional to play the role of a data scientist?
Discuss the responsibilities of a data scientist.









[10]



4.

What is meant by predictive analytics? With suitable examples explain the need of it for
the market/ industry.















[10]

OR

5.

Describe the features of IBM SPSS tool for data analytics.





[10]


6.

With relevant examples discuss the techniques to optimize map reduce jobs.

[10]

OR

7.

What are the various components in Hadoop eco system? Briefly explain each component
use.





















[10]



8.

What are the main features of NoSQL? Can it eliminate RDBMS? Explain the role of
NoSQL in big data handling.













[10]

OR

9.

What is a cluster? What is its importance? Discuss the features of Hadoop cluster for
HDFS.



















[10]



10.

What is sentiment analysis? Demonstrate it on Twitter data. Assume suitable tweets to
explain your answer.















[10]

OR

11.

Explain the steps in text mining process and give the famous applications of text mining.






















[10]



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