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