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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

This post was last modified on 17 March 2023


R17

Code No: 844AM

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JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

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MCA V Semester Examinations, December - 2019

BIG DATA ANALYTICS

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Time: 3hrs




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Max.Marks:75

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S

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

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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.


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PART - A



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5 ? 5 Marks = 25

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

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[5]

b) Differentiate between monetized analytics and operational analytics.


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[5]

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

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[5]

d) What is NoSQL? Where is it used?

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[5]

e) List the key elements of social media.


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[5]

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PART - B

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5 ? 10 Marks = 50

2.

Describe three types of analytics and various analytical approaches typically associated

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with big data.




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[10]

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OR

3.a)

Explain the importance of parallel computing for big data.

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b)

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

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[5+5]

4.

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

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[10]

OR

5.a)

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Illustrate various phases of analysis process.

b)

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Make a brief comparison of R and SAS tools.




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[5+5]


6.

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

[10]

OR

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7.a)

Briefly discuss any five hadoop-specific file system types.

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b)

What is the functionality of Hadoop YARN?


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[5+5]


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8.a)

Discuss the advantages of shared nothing architecture.

b)

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List the components of the Hadoop ecosystem.



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[5+5]

OR

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9.

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

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[10]

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

analysis?

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



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[5+5]

OR

11.a) What is the importance of location-based tracking tools?

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b) Differentiate between internal and external mobile analytics tools.



[5+5]

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