AKTU Introduction to Data Analytics and Visualization (BCDS501) Question Paper 2024-25

Note: Attempt all Sections. In case of any missing data; choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 7 = 14 marks

1. What are the challenges and solutions associated with scaling analytics in modern organizations?
2. How do modern tools bridge the gap between analysis and reporting? 1 K
3. Compare and contrast Bayesian modeling with neural networks in terms 2 K 3 , of their applications. K
4. How do linear and nonlinear dynamics influence the accuracy of 2 K 3 , predictions?
5. Analyze the challenges of real-time sentiment analysis.
6. How do methods like CLIQUE and ProCLUS overcome traditional 4 K , clustering limitations?
7. What are the trade-offs between static and dynamic visualizations?

Section B

Q2. Attempt any three of the following · 7 × 3 = 21 marks

1. Describe the key characteristics of Big Data. How do these characteristics necessitate the development of advanced analytics platforms?
2. Explain the concept of rule induction in data mining. How is it used to 2 K 3 , derive meaningful patterns from datasets?
3. Describe the concept of decaying windows in stream analytics. How 3 K does it help in managing memory and computational resources?
4. Compare and contrast hierarchical clustering and K-means clustering. 4 K 2 , What are the advantages and disadvantages of each?
5. Discuss the importance of figure captions in visual interfaces. How do they enhance the interpretability of data visualizations? K

Section C

Q3

Attempt any one part of the following · 7 × 1 = 7 marks

1. How has the need for data analytics evolved with the advent of IoT and real-time systems? Provide relevant examples.
2. Define the term 'analytic lifecycle.' How do the roles of stakeholders vary across its different phases?

Q4

Attempt any one part of the following · 7 × 1 = 7 marks

1. Critically analyze the challenges of multivariate analysis in high- 2 K , dimensional datasets. How can these challenges be addressed?
2. How do stochastic search methods differ from deterministic 2 K 3 , optimization techniques? Provide use cases for each.

Q5

Attempt any one part of the following · 7 × 1 = 7 marks

1. Discuss the role of Real-Time Analytics Platforms (RTAP) in modern enterprises. Provide a case study to support your explanation.
2. Describe the steps involved in building a real-time stock market 3 K prediction system using stream analytics. What are the key considerations?

Q6

Attempt any one part of the following · 7 × 1 = 7 marks

1. What is parallelism in clustering algorithms? How does it improve 4 K , performance in handling large datasets?
2. How is clustering applied to streaming data? Discuss the modifications 4 K 2 , needed in traditional clustering algorithms for stream analytics.

Q7

Attempt any one part of the following · 7 × 1 = 7 marks

1. Explain the concept of navigation links in data visualization. How do they improve user interaction with complex datasets? K
2. Explain the role of human vision in designing effective data visualizations. How do space and time limitations influence this process?

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