UOTC Big Data Science Analyti

Paper Type: Research Paper

Topic: Big Data Science Analytics and Blockchain

Task: Conduct a literature review on the issue of Data Science and Big Data Analytics, and how companies are handling the complexity of handling the vast amounts of data they collect and have to safeguard. Discuss problems that companies are experiencing and what research has been done to manage and understand information from their data, while trying to minimize damage from data disclosure.

Focus Area: You are to review the literature on Enterprise Data Science and Big Data Analytics and discuss problems and gaps that have been identified in the literature. You will expand on the issue and how researchers have attempted to examine that issue by collecting data – you are NOT collecting data, just reporting on how researchers did their collection.


Introduction/Background: Describe the issue, Discuss the problem, and elaborate on any previous attempts to examine that issue.

Research Questions: In your identified problem area that you are discussion, what were the research questions that were asked?

Methodology: What approach did the researcher use, qualitative, quantitative, survey, case study? Describe the population that was chosen.

Data Analysis: What were some of the findings, for example, if there were any hypotheses asked, were they supported?

Conclusion: What was the conclusion of any data collections, e.g., were research questions answered, were hypotheses supported?

Discussion: Here you can expand on the research and what the big picture means, how do the results found in your literature review help organizations with the problems of handling, managing and safeguarding all this data. What do you see as long-term impacts and what further research could be done in the field?


Need minimum 2000 Words (Diagrams or Graphs Not Included)

Need minimum 10 Scholarly APA References

Need 2 or 3 Diagrams or Graphs of the Statical Analysis during survey

Need PPT with 12 Slides (Background of the problem, Research Questions, Methodology, Data Analysis (Add Graphs), Conclusion, Discussion).

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