WEEK3-DISCUSSION3-Data Science & Big Data Analy

Course: Data Science & Big Data Analy

LATE SUBMISSION WILL NOT BE ACCEPTED BY PROF.

Due Date – 1 day

Discussion Question:   Big Data Visualization 

Several Big Data Visualization tools have been evaluated in this weeks  paper. While the focus was primarily on R and Python with GUI tools, new  tools are being introduced every day. Compare and contrast the use of R  vs Python and identify the pros and cons of each. Provide an example of  both programming languages with coding examples as well as your  experience in using one or both programming languages in professional or  personal work. If you have no experience with either language, please  discuss how you foresee using either/both of these languages in  visualizing data when analyzing big data. 

Prof. Guidelines 

• Provide extensive additional information on the topic


• Explain, define, or analyze the topic in detail


• Share an applicable personal experience


• Provide an outside source (for example, an article from the   University Library) that applies to the topic, along with additional   information about the topic or the source (please cite properly in APA)


• At least one scholarly source should be used in the initial   discussion thread. Be sure to use information from your readings and   other sources from the UC Library. Use proper citations and references   in your post.

Books and Resources 

Required Text

Eyupoglu, C. (2019). Big Data in Cloud Computing and Internet of Things. 2019   3rd International Symposium on Multidisciplinary Studies and  Innovative  Technologies (ISMSIT), Multidisciplinary Studies and  Innovative  Technologies (ISMSIT), 2019 3rd International Symposium On, 1–5. https://doi.org/10.1109/ISMSIT.2019.8932815

L. Zhao, Y. Huang, Y. Wang and J. Liu, "Analysis on the Demand of Top   Talent Introduction in Big Data and Cloud Computing Field in China   Based on 3-F Method," 2017 Portland International Conference on   Management of Engineering and Technology (PICMET), Portland, OR, 2017,    pp. 1-3. https://doi.org/10.23919/PICMET.2017.8125463

Saiki, S., Fukuyasu, N., Ichikawa, K., Kanda, T., Nakamura, M.,   Matsumoto, S., Yoshida, S., & Kusumoto, S. (2018). A Study of   Practical Education Program on AI, Big Data, and Cloud Computing  through  Development of Automatic Ordering System. 2018 IEEE  International  Conference on Big Data, Cloud Computing, Data Science  & Engineering  (BCD), Big Data, Cloud Computing, Data Science &  Engineering (BCD),  2018 IEEE International Conference on, BCD, 31–36. https://doi.org/10.1109/BCD2018.2018.00013

Psomakelis, E., Aisopos, F., Litke, A., Tserpes, K., Kardara, M., & Campo, P. M. (2016). Big   IoT and social networking data for smart cities: Algorithmic   improvements on Big Data Analysis in the context of RADICAL city   applications.

Liao, C.-H., & Chen, M.-Y. (2019). Building social computing   system in big data: From the perspective of social network analysis. Computers in Human Behavior, 101, 457–465. https://doi.org/10.1016/j.chb.2018.09.040

"APA Format" 

https://academicwriter.apa.org/6/ 

"NO PLAGIARISM" 

Plagiarism includes copying and pasting material   from the internet into assignments without properly citing the source   of the material.