MUTHAYAMMAL ENGINEERING COLLEGE
(An Autonomous Institution)
(Approved by AICTE, New Delhi, Accredited by NAAC & Affiliated to Anna University)
Rasipuram - 637 408, Namakkal Dist., Tamil Nadu.
Department of Master of Computer Applications
Question Bank - Academic Year (2020-21)
Course Code & Course Name
:
19CAB13 & Big Data Analytics
Year/Sem/Sec
:
I / II
Unit-I: INTRODUCTION TO BIG DATA
Part-A (2 Marks)
1.
What is Big Data?
2.
Differentiate Analysis from Reporting.
3.
What is predictive analysis?
4.
Define Big Data and mention any two sources of generating it.
5.
Explain sampling distribution with an example.
6.
What are the three V’s of Big Data?
7.
What is sampling?
8.
Explain prediction error.
9.
Write any two applications of Big Data Analytics.
10.
What are the types of analytics?
Unit-II : MINING DATA STREAMS
Part-A (2 Marks)
1.
What do you mean by Stream computing?
2.
Explain Filtering streams.
3.
What is decaying window?
4.
What is data stream model?
Part-B (16 Marks)
1.
Explain in detail the modern data analytic tools.
(16)
2.
Explain in detail the intelligent data analysis.
(16)
3.
Explain about i. Challenges of conventional systems (8)
ii. Analytical processes and tools (8)
iii.
4.
Explain in detail Analysis Vs Reporting.
(16)
5.
Discuss Sampling distribution concepts
(16)
5.
What is meant by one-time queries?
6.
What is Bloom Filter?
7.
What is Sentiment Analysis?
8.
. List out the applications of RTAP.
9.
What is Stock Market prediction?
10.
How will you count ones in a window?
Unit-III : HADOOP ENVIRONMENT
Part-A (2 Marks)
1.
What is Hadoop?
2.
What are the components of HDFS?
3.
What is MapReduce and what are its phases?
4.
Explain YARN.
5.
What are the components of Hadoop?
6.
What is Hadoop and what are its components?
7.
What are the phases in MapReduce?
8.
Explain Scaling Out.
9.
How does the namenode track the existence of data node?
10.
What are the functions of Datanode?
Unit-IV : DATA ANALYSIS SYTEMS AND VISUALIZATION
Part-A (2 Marks)
1.
Explain Page Rank.
2.
What are basic charts?
Part-B (16 Marks)
1.
Discuss the stream data model and architecture
(16)
2.
Discuss the RealTime Analytics Platform Applications.
(16)
3.
Discuss the Filtering Streams.
(16)
4.
Discuss Real Time Sentiment Analysis.
(16)
5.
Write a detailed note on estimating moments.
(16)
Part-B (16 Marks)
1.
Explain in detail the HDFS.
(16)
2.
Discuss the MapReduce process.
(16)
3.
Explain the procedure in setting up a hadoop cluster.
(16)
4.
Write about the wordcount mapreduce hadoop application.
(16)
5.
Explain the MapReduce architecture and it’s working.
(16)
3.
Explain Link spam.
4.
What is visualization?
5.
What is Recommendation system?
6.
What do you mean by Collaborative filtering?
7.
Explain Content based recommendation.
8.
What is meant by dimensionality reduction?
9.
What are the three major goals in visualization?
10.
Explain interactive visualization.
Unit-V : DATA ANALYTICS USING PYTHON
Part-A (2 Marks)
1.
What is data analytics?
2.
How will you create a Series?
3.
What is Jupiter notebook?
4.
What do you mean by data frame?
5.
What is List?
6.
How will you display the content of a data frame?
7.
Write the procedure to add a column to a data frame.
8.
How will you create a sub data frame?
9.
Explain descriptive statistics.
10.
How to add a compute column in a data frame?
Course Faculty
HoD
Part-B (16 Marks)
1.
Explain the visual data analysis techniques.
(16)
2.
Write a detailed note on recommendation systems.
(16)
3.
Explain the efficient computation of PageRank.
(16)
4.
Discuss the Model for Recommendation Systems.
(16)
5.
Discuss visual interactive technique’s systems and applications.
(16)
Part-B (16 Marks)
1.
Write a detail note on Pandas module.
(16)
2.
Explain Series, Data Frame and Panel.
(16)
3.
Discuss about different ways of creating data frames.
(16)
4.
Explain the procedure to work with columns and rows in a data frame.
(16)
5.
Explain the different ways of handling missing data.
(16)
