JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD
JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD MCA 2019 BIG DATA ANALYTICS Previous Question Paper (December - 2019 - R15)
Note: This question paper contains two parts A and B. 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.
Part A
List the types and sources of big data.
Answer
Big data is categorized into three types: Structured data (highly organized, residing in relational databases), Unstructured data (no predefined format, such as videos, images, and social media posts), and Semi-structured data (contains tags or markers, such as XML, JSON, or sensor logs). The primary sources include Social Media (user-generated content), Machine-generated data (IoT sensors, logs, and telemetry), Transactional data (e-commerce and banking records), and Public web data (web scraping and open government datasets).
Differentiate between monetized analytics and operational analytics.
Answer
Monetized analytics focuses on deriving direct revenue or competitive advantage by selling data insights or creating new data-driven products. It is externally oriented, aimed at understanding customer behavior to increase profitability. In contrast, Operational analytics is internally oriented, focusing on optimizing business processes, improving efficiency, and monitoring real-time system performance. While monetized analytics targets strategic growth and market positioning, operational analytics targets cost reduction and streamlined workflows.
What points to be considered in designing a file to support Map Reduce implementation?
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What is NoSQL? Where is it used?
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List the key elements of social media.
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Part B
Describe three types of analytics and various analytical approaches typically associated with big data.
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Explain the importance of parallel computing for big data.
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What are the key questions to be answered by all organizations stepping into analytics?
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Explain the differences between reporting and analysis with suitable example scenarios.
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Illustrate various phases of analysis process.
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Make a brief comparison of R and SAS tools.
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Discuss the role of HBase in big data processing with suitable examples.
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Briefly discuss any five hadoop-specific file system types.
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What is the functionality of Hadoop YARN?
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Discuss the advantages of shared nothing architecture.
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List the components of the Hadoop ecosystem.
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What are the limitations of relational database management system? Explain how hadoop has overcome them.
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What parameters are applied to classify the given text in the process of sentiment analysis?
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Discuss briefly online tools used to perform sentiment analysis.
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What is the importance of location-based tracking tools?
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Differentiate between internal and external mobile analytics tools.
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