Fundamentals of Big Data & Business Analytics - NMIMS Solved assignments 2025 Latest

 

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Fundamentals of Big Data & Business Analytics

Jun 2025 Examination

 

 

Q1. Indian Railways: Operations and Passenger Experience Optimization Indian Railways manages    millions of daily passengers    and collects vast amounts of data from    ticket bookings, train schedules, GPS tracking, passenger complaints, and real-time weather reports. Discuss how    descriptive analyticscan help monitor train delays and passenger demand, how    predictive analytics    can anticipate congestion, maintenance issues, and peak travel periods, and how    prescriptive analytics    can optimize train scheduling, crowd control, and service reliability. (10 Marks)

 

 

Q2. Big Data in Financial Markets

A stock trading platform collects vast amounts of data from    market transactions, investor sentiment on social media, economic reports, and algorithmic trading bots. Explain how firms handle    data ingestion, processing, storage, and management    using    big data frameworks    such as    distributed computing, cloud storage, and real-time streaming. Discuss how this data is analyzed to detect fraud, optimize trading strategies, and provide personalized investment recommendations (10 Marks)

 

Q3 (A)  Visualization for Urban Traffic Management

A city’s traffic control system collects data from  GPS trackers, CCTV feeds, road sensors, and mobile navigation apps  to ease congestion. Explain how  descriptive analytics  can identify high-traffic zones and discuss how    visualization tools (heatmaps, real-time dashboards, interactive reports)  can help city planners make data-driven decisions. (5 Marks)

 

 

Q3 (B) Social Media and Web Analytics for E-Commerce

An online retailer wants to leverage    customer reviews, social media trends, browsing behavior, and mobile app data    to improve sales. Discuss how    social media sentiment analysis, mobile analytics, and web tracking tools    can generate insights on customer preferences. Explain how    predictive and prescriptive analytics    can drive personalized marketing, optimize product recommendations, and improve customer retention. (5 Marks)

 

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