1. Title introduction The CEO comes to your office and describes that Globalytics needs to…

1. Title

introduction

The CEO comes to your office and describes that Globalytics needs to urgently address certain business scenarios that cannot be adequately addressed by the analytical techniques that you’ve been using thus far and which may require learning and applying web and text mining methods. Also, the scenarios presented require analyzing large datasets.

As the Chief Analytics Officer, you ask DART, the Data Action Response Team, to look into the feasibility of using one of these techniques, learn, and then actually use the selected technique to demonstrate its effectiveness in identifying and addressing the problem. You and the team are to collaboratively analyze the dataset and prepare a group report.

Steps to Completion

(2) Locate a large dataset that relates to the domain that interests the team.

(3) Import the dataset into RStudio. Prepare and analyze the data.

(4) Prepare a formal data mining study report that is described in the next section.

Deliverables

The report should include

review necessary literature and briefly discuss the text choice and the text analysis methods you have chosen to work on and the business scenario that your analysis would address.

The report should be 12-15 pages long including references but excluding the title page. Also submit the script of your R program. You may either prepare your report by describing each of the phases in the CRISP-DM data mining process, or by following the format below:

Introduction: Objectives, rationale for the study and scope.

Analysis method (include a short description of the data, link to data file, data mining algorithm, and how it was applied),

Results (narrative form),

Interpretation of results,

Limitations of the analysis,

Suggestions for a subsequent analysis, and

RUBIRIC

5. Rubric

Criteria	Weight (%)	Score (0-100)	Totals (Wt x Score)
Understand the concept and role of the data mining method or algorithms used	40
Demonstrate knowledge of using R for data mining	30
Demonstrate critical thinking and originality	20
Exhibit strong presentation skills	10
Peer evaluation adjustment, if necessary
Total	=SUM(ABOVE) 100