Total No. of Questions : 8] SEAT No.

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P826 [Total No. of Pages : 2

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[5870] - 1149

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T. E. (Information Technology)

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DATA SCIENCE AND BIG DATA ANALYTICS

2:5
(2019 Pattern ) (Semester - II) (314452)

02 91
8:3
Time : 2½ Hours] [Max. Marks : 70

0
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2/0 13
Instructions to the candidates:
1) Answer Q.1, or Q.2, Q.3 or Q.4, Q.5 or Q.6, Q.7 or Q.8.
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2) Neat diagrams must be drawn wherever necessary.
7/2
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3) Figures to the right side indicate full marks.

4) Assume the suitable data, if necessary.
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80

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Q1) a) Explain Big data Ecosystem with suitable diagram. [7]

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b) Explain anatomy of File read and write in HDFS. [7]
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3s
c) Write and explain any two Hadoop shell commands. [4]
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2:5
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OR
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8:3
30

Q2) a) Explain Map Reduce with proper diagram for word count example. [7]
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b) Explain Google file system. [7]

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c) Explain ETL processing. [4]

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Q3) a) Explain different steps in Data Analytics Project Life cycle [7]

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b) Draw and explain Architecture of HIVE. [7]
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c) Explain different data transformation techniques. [3]
8.2

3s

OR
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2:5
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Q4) a) Explain different kinds of Big Data Analysis. [7]

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8:3
30

b) How data can be ingested in python. Write syntax in python for the
20

same. [7]
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02

c) Explain role of visualization in big data analytics. [3]

7/2
GP
2/0
CE
80

Q5) a) Explain different techniques of Big Data visualization. [7]

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b) Explain challenges in Big data visualization. [7]

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c) Write two data visualization functions from matplotlib. [3]

8.2

OR
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[5870] - 1149 1
P.T.O.
Q6) a) Explain different tools for data visualization. [7]

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b) Explain scatter plot, histogram and heat map with example. [7]

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c) Write two data visualization functions from seaborn. [3]

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2:5
02 91
8:3
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Q7) a) How Social Media analytics helps in value creation? Explain with suitable

20
examples. 2/0 13 [7]
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b) Explain in brief data analytics life cycle. [7]
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c) Explain big data value terminology. [4]

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80

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OR

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Q8) a) What is text mining? Draw and explain text mining architecture and its
8.2

3s
use. [7]
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b) Explain Big data analytics in research. [7]
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8:3
30
20

c) Explain big data impact on organizations. [4]

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80

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[5870] - 1149 2
Total No. of Questions : 8 SEAT No. :

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PA-1508 [Total No. of Pages : 2

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[5926]-128

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T.E. (Information Technology)

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02 91
DATA SCIENCE AND BIG DATA ANALYTICS

9:5
(2019 Pattern) (Semester-II) (314452)
0
30
Time : 2½ Hours]
6/0 13 [Max. Marks : 70
0
Instructions to the candidates:
1/2
.23 GP

1) Answer Q1 or Q2, Q3 or Q4, Q5 or Q6, Q7 or Q8.

2) Neat diagrams must be drawn wherever necessary.
E
81

3) Figures to the right indicate full marks.

8
C

23
4) Assume suitable data, if necessary.

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16

Q1) a) i) Explain Google File system and its advantages. [5]

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8.2

2s
ii) Explain ETL in Big data. [5]
.24

0:4
91
b) Explain Hadoop distributed file system. [8]
49

9:5
30
30

OR
01
02

Q2) a) i) Write 5 Hadoop Shell commands. [5]

1/2
GP

ii) Explain Role Job tracker and Task Tracker in Hadoop Architecture.
6/0

[5]
CE
81

8
23
b) Explain Map Reduce with proper diagram for word count example. [8]
.23

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16

tat
8.2

2s

Q3) a) Explain different types of Big Data Analysis techniques. [8]

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0:4

b) i) Explain Different Data Transformation techniques. [3]

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49

9:5

ii) What is dataset? Explain with python syntax of 2 different types of

30

dataset used in Big data. [6]

30
01
02
1/2

OR
GP
6/0

Q4) a) i) Explain Mean, Mode and variance and standard deviation with
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suitable example. [8]

81

ii) Explain Data Standardization. [3]

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b) Draw and explain Architecture of HIVE. [6]

16
8.2
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P.T.O.
49
Q5) a) i) How data visualization help Big data Analytics. [4]

8
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ii) List the conventional Data visualization tools. Explain any Two. [6]

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b) Explain data visualization with the help of example? What are the

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advantages of data visualization? [8]

2s
OR

0:4
02 91
Q6) a) Explain any 4 Types of data visualization with example. [8]

9:5
0
b) i) Explain different data visualization tools. [6]

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6/0 13
ii) Explain Data Visualization with Tableau. [4]
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1/2
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Q7) a) Explain Text mining with example. [8]

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b) Explain Big Data Analytics Challenges in brief. [9]

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8
C

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OR

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Q8) a) Explain four Big Data use cases. [8]
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2s
b) Explain types of Mobile Analytics. [9]
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30

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2s
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[5926]-128 2
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Total No. of Questions : 8] SEAT No. :

8
23
P490 [Total No. of Pages : 2

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T.E. (I.T.)

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1:3
DATA SCIENCE AND BIG DATA ANALYTICS

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(2019 Pattern) (Semester-II) (314452)

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Time : 2½ Hours]
3/0 13 [Max. Marks : 70
0
6/2
Instructions to the candidates:
.23 GP

1) Answer Q.1 or Q.2, Q.3 or Q.4, Q.5 or Q.6, Q.7 or Q.8.

E

2) Figures to the right indicate full marks.

82

8
C

23
3) Neat diagrams must be drawn wherever necessary.

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4) Assume suitable data, if necessary.
16

tat
8.2

9s
Q1) a) Explain Google file system and its advantages. [10]
.24

1:3
91
b) Explain Hadoop distributed file system [8]
49

0:4
30

OR
31
01

Q2) a) Why map reduce is required in Hadoop? Explain the stages involved in
02

map reduce task with a suitable example? [9]

6/2
GP
3/0

b) Describe the various types of NoSQL Databases with example and also
CE

compare them. [9]

82

8
23
.23

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16

Q3) a) Explain Mean, Mode and variance and standard deviation with suitable
tat
8.2

example. [9]
9s
.24

1:3

b) Draw and explain Architecture of HIVE [8]

91
49

0:4

OR
30
31

Q4) a) Explain Min-max scaling. For the following dataset carry out min-max
01
02

Scaling, X=24, 28, 53, 30, 40, 18, 15, 21 [9]

6/2
GP

b) What is data Wrangling? Why do you need it? explain data Wrangling
3/0

methods? [8]
CE
82
.23

Q5) a) Explain any 4 Types of data visualization with example. [9]

16

b) Explain different data visualization tools. [9]

8.2

OR
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49

P.T.O.
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Q6) a) Explain data visualization with the help of example? What are the

23
advantages of data visualization? [9]

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b) Explain Data Visulization with Tableau. [9]

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1:3
02 91
Q7) a) Explain Big Data Analytics Challenges in brief. [9]

0:4
0
b) Explain types of Mobile Analytics. [8]

31
3/0 13
OR
0
6/2
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Q8) a) What is Porters valuation creation model? Explain porter’s value chain
analysis. [9]
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b) What is social media analytic? Explain the process of social media data

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analytic. [8]
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31
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[6003]-711
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2
Total No. of Questions : 8] SEAT No. :

8
23
P-7626 [Total No. of Pages : 2

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[6180]-146

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T.E. (Information Technology)

8:3
02 91
DATA SCIENCE AND BIG DATA ANALYTICS

9:5
0
(2019 Pattern) (Semester - II) (314452)

30
3/1 13
0
Time : 2½ Hours] [Max. Marks : 70
2/2
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Instructions to the candidates:

1) All questions are compulsory.
E
81

8
C

23
2) Figures to the right indicate full marks.

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Q1) a) Explain the process of reading and writing a file in HDFS with neat
8.2

7s
diagram. [8]
.24

8:3
91
b) List and explain any four Hadoop shell commands with syntax. [4]
49

9:5
c) Differentiate between SQL and NoSQL databases with example.What
30
30

is the need to develop big data applications using NoSQL databases?

01
02

[6]
2/2
GP

OR
3/1

Q2) a) What is the need of map reduce in Big Data? Explain the stages involved
CE
81

8
in map reduce task with a suitable example? [9]

23
.23

b) Explain Hadoop ecosystem in detail.

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[9]
16

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8.2

7s

Q3) a) What is data wrangling? Why do you need it? Explain data wrangling
.24

8:3
91

methods? [9]
49

9:5
30

b) What is categorical variable? Why do you need categorical variable

30

encoding? With an example, explain one-hot encoding. [9]

01
02

OR
2/2
GP

Q4) a) Draw and explain Architecture of HIVE. [8]

3/1
CE
81

b) How missing values and categorical variables are preprocesses before

building model? Explain with suitable example. [4]
.23

c) Explain z-score normalization. For the following dataset carry out

16

z-score normalization (standardization), X = 23, 29, 52, 31, 45, 19,

8.2

18, 27. [6]

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49

P.T.O.
Q5) a) What is Data Visualization? What are the major challenges in big data

8
visualization and how to overcome these challenges? [6]

23
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b) Explain various techniques for visual data representation. [6]

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7s
c) Explain the following data visualization techniques. [5]

8:3
02 91
i) Candela

9:5
0
30
ii) D3.js
3/1 13
OR
0
2/2
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Q6) a) Explain data visualization with respect to l-D, 2-D, 3-D data. [6]
E
81

8
b) Explain various analytical techniques used in big data visualization.
C

23
[6]

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16

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c) Draw histogram with a suitable example and explain its usage. [5]
8.2

7s
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8:3
91
49

9:5
Q7) a) What is Porters valuation creation model? Explain porter’s value chain
30
30

analysis. [9]
01
02

b) What is social media analytics? Explain the process of social media

2/2
GP

data analytics. [8]

3/1
CE

OR
81

8
23
.23

Q8) a) What is text mining? Draw and explain text mining architecture and its
ic-
16

use. [8]
tat
8.2

7s

b) Explain primary activities of Michal Porters value chain. [5]

.24

8:3
91
49

c) How mobile analytics is different from social media analytics? [4]

9:5
30
30
01
02


2/2
GP
3/1
CE
81
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16
8.2
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[6180]-146 2
Total No. of Questions : 8] SEAT No. :

8
23
PB3866 [Total No. of Pages : 2

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[6262]-130

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T.E. (Information Technology)

0:1
02 91
DATA SCIENCE AND BIG DATA ANALYTICS

9:4
0
(2019 Pattern) (Semester - II) (314452)

40
7/0 13
Time : 2½ Hours] [Max. Marks : 70
0
5/2
Instructions to the candidates:
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1) All questions are compulsory.

E

2) Figures to the right indicate full marks.

81

8
C

23
ic-
Q1) a) Explain all the steps for writing a file in HDFS with neat diagram. [8]
16

tat
8.2

b) Describe the various types of NoSQL Databases with example and also

3s
.24

0:1
compare them. [10]
91
49

9:4
OR
30
40

Q2) a) Why map reduce is required in Hadoop? Explain the stages involved in
01
02

map reduce task with a suitable example? [9]

5/2
GP

b) What is Hadoop Distributed system? What is the advantage of heart bit

7/0

message in Hadoop. [9]

CE
81

8
23
.23

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16

Q3) a) Compare HBASE and HIVE with suitable parameters. [8]

tat
8.2

3s

b) How missing values are filled in Pandas Data Frame with zeros? Assume
.24

0:1

suitable data. [3]

91
49

9:4

c) Explain Min-max scaling. For the following dataset carry out min-max
30
40

Scaling, X = 24,28,53,30,40,18,15,21. [6]

01
02

OR
5/2
GP
7/0

Q4) a) What is categorical variable? Why do you need categorical variable

CE
81

encoding? With an example, explain one-hot encoding? [8]

.23

b) What is data wrangling? Why do you need it? Explain data wrangling
16

methods? [9]
8.2
.24
49

P.T.O.
Q5) a) How Data Visualization is important in Big Data? Explain challenges to

8
23
big data visualization? [6]

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b) Explain various techniques for visual data representation. [6]

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3s
c) Explain the following data visualization techniques. [6]

0:1
02 91
i) Google Chart API

9:4
0
40
ii) D3.js
7/0 13
OR
0
5/2
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Q6) a) Explain data visualization with respect to l-D, 2-D, 3-D data? [6]
E
81

b) Explain various analytical techniques and tools used in data visualization.[6]

8
C

23
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c) Draw boxplot with a suitable example and explain its usage. [6]
16

tat
8.2

3s
.24

Q7) a) What is text mining? Draw and explain text mining architecture and its
0:1
91
use. [8]
49

9:4
30

b) Explain primary activities of Michal Porters value chain. [5]

40
01
02

c) How mobile analytic is different from social media analytic? [4]

5/2
GP

OR
7/0
CE

Q8) a) What is Porters valuation creation model? Explain porter’s value chain
81

8
23
analysis. [9]
.23

b) What is social media analytic? Explain the process of social media data. ic-
16

tat
analytic. [8]
8.2

3s
.24

0:1
91
49

9:4

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