Describe the Technological Challenges Posed by Big Data DATA-SCIENCE-FOUNDATIONS Practice Questions (Page 7)

Questions 31–35

1. 31application · medium

   A research institute needs to run a complex simulation that processes 50 TB of climate data. The simulation currently takes 3 weeks to complete on their high-performance computing cluster. The researchers need results in under a week to meet a publication deadline. What is the most effective way to address this processing challenge?

   • AAdd more compute nodes to the cluster to parallelize the simulation.
   • BReduce the data size by sampling only 10% of the data.
   • CMove the data to a faster storage system, such as SSDs.
   • DOptimize the simulation algorithm to reduce the number of computations.
   Reveal Solution Discussion Select an answer first
2. 32application · medium

   A city's traffic department collects data from GPS sensors on buses, social media posts about traffic, and manual incident reports. When building a real-time congestion map, the department finds that GPS data sometimes has gaps, social media posts are often inaccurate, and manual reports are delayed. What is the most significant challenge they must address before the map can be trusted?

   • AVariety challenge; convert all data to a single format to make it consistent.
   • BVolume challenge; collect more data from additional sensors to fill the gaps.
   • CVeracity challenge; implement data quality checks and cross-validation across the multiple sources.
   • DVelocity challenge; process the data faster to reduce the delay in manual reports.
   Reveal Solution Discussion Select an answer first
4. 33application · medium

   A ride-sharing company needs to match drivers with riders in real time. The system receives millions of GPS location updates per minute and must process them with minimal latency to provide accurate ETAs and surge pricing. What is the most appropriate technology approach for this real-time processing challenge?

   • AStore all GPS updates in a data warehouse and run batch queries every hour.
   • BUse a traditional relational database to store and query the GPS data.
   • CProcess the data on a single powerful server to avoid network latency.
   • DUse a stream processing framework that ingests and analyzes events continuously.
   Reveal Solution Discussion Select an answer first
5. 34foundation · easy

   Which of the following best describes a difficulty in processing and analyzing Big Data?

   • AThe data is always small enough to process on a single machine.
   • BThe need for specialized distributed computing frameworks to handle the scale.
   • CThe data is always structured and easy to query.
   • DThe data is always stored in a relational database.
   Reveal Solution Discussion Select an answer first
6. 35application · medium

   A multinational corporation's data science team uses data from various regional offices. Each office has its own data quality standards, and some offices collect data that is not compliant with the company's new privacy policy. The central team needs to ensure consistent quality and compliance across all data. What is the most appropriate approach?

   • ALet each regional office continue to manage its own data independently.
   • BDelete all data that does not meet the company's privacy policy.
   • CEstablish a centralized data governance framework with clear policies for data quality, access, and usage.
   • DCentralize all data into a single database to ensure consistency.
   Reveal Solution Discussion Select an answer first