AKTU Data Analytics (KCS051) Question Paper 2020-21

Note: Attempt all Sections. If require any missing data; then choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 10 = 20 marks

1. What are the different types of data?
2. Explain decision tree.
3. Give the full form of RTAP.
4. List various phases of data analytics lifecycle.
5. Explain the role of Name Node in Hadoop.
6. Discuss heartbeat in HDFS.
7. Differentiate between an RDBMS and Hadoop.
8. Write names of two visualization tools.
9. How can you deal with uncertainty?
10. Data sampling is very crucial for data analytics. Justify the statement.

Section B

Q2. Attempt any three of the following

1. Explain K-Means algorithms. When would you use k means? State weather the statement “K-Means has an assumption each cluster has a roughly equal number of observations” is true or false. Justify your answer
2. Illustrate and explain the steps involved in Bayesian data analysis.
3. Suppose that A, B, C, D, E and F are all items. For a particular support threshold, the maximal frequent item sets are {A, B, C} an {D, E}. What is the negative border?
4. Discuss any two techniques used for multivariate analysis.
5. Design and explain the architecture of data stream model.

Section C

Q3

Attempt any one part of the following

1. Describe the architecture of HIVE with its features.
2. Brief about the main components of MapReduce

Q4

Attempt any one part of the following

1. Describe any two data sampling techniques.
2. Explain any one algorithm to count number of distinct elements in a Data stream.

Q5

Attempt any one part of the following

1. Brief about the working of CLIQUE algorithm.
2. Cluster the following eight points (with (x, y) representing locations)
   into three clusters: A1(2, 10), A2(2, 5), A3(8, 4), A4(5, 8), A5(7, 5),
A6(6, 4), A7(1, 2), A8(4, 9)
   Initial cluster centers are A1(2, 10), A4(5, 8) and A7(1, 2). The distance function between two points a = (x1, y1) and b = (x2, y2) is defined as-
   Use K-Means Algorithm to find the three cluster centers after the second iteration

Q6

Attempt any one part of the following

1. What is prediction error? State and explain the prediction error in regression and classification with suitable example.
2. Given data = {2, 3, 4, 5, 6, 7; 1, 5, 3, 6, 7, 8}. Compute the principal component using PCA Algorithm.

Q7

Attempt any one part of the following

1. Develop and explain the data analytics life cycle
2. Distinguish between supervised and unsupervised learning with example.

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