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Data Science and Big Data Literature Review Test Submit Assignment Due Sep 17 by

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Data Science and Big Data Literature Review Test
Submit Assignment
Due Sep 17 by 11:59pm
Points 11
Submitting a file upload
Available after Sep 1 at 12am
Data Science Literature Review Test
INF 160 Introduction to Data Science
About the test:
Total points: 100 (carries 11% of the final grade)
Each question worth 20 points 
Must answer all question to achieve a maximum of 20 points each
Each answer must contain a minimum of 300 words. 
Submit responses as a word document in Canvas Assignment page. 
Questions:
Define data science and big data in your own words. Why data science and big data matters?
Write down some applications of data science/big data in the real world.
What are the five “V”s of big data? Explain those. What is the process of data science research/project?
What are some challenges of big data research? Explain those. 
How do you intend to prepare yourself as a data scientist? Explain some areas of data science you will use in your foreseeable professional life as a data scientist. 
Helpful Articles:
Wikipedia entry on Data Science: https://en.wikipedia.org/wiki/Data_science (Links to an external site.) 
Data Scientist_ The Sexiest Job of the 21st Century.pdf from (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century (Links to an external site.))
Popularity of Data Science Software: http://r4stats.com/articles/popularity/ (Links to an external site.) 
Data Science Core Knowledge and Skills: http://datasciences.org/ (Links to an external site.) 
Big Data Analytics and Capabilities: https://www.researchgate.net/profile/Ilias_Pappas/publication/318449845_Big_data_analytics_capabilities_a_systematic_literature_review_and_research_agenda/links/596bea2fa6fdcc18ea7927d0/Big-data-analytics-capabilities-a-systematic-literature-review-and-research-agenda.pdf (Links to an external site.)
Big Data: The Age of Big Data.pdf
Big Data Impacts: SPECIAL_ISSUE_BUSINESS_INTELLIGENCE_RESE.pdf 
Big Data Challenges: Critical Questions for Big Data.pdf
Big Data Analytics: Big_Data_Analytics.pdf

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