03 May develop a data-analytics plan using the CRISP-DM framework. As a plan it should propose or outline, as specifically as possible, the applicatio
develop a data-analytics plan using the CRISP-DM framework. As a plan it should propose or outline, as specifically as possible, the application of the CRISP-DM framework to a “business” problem of interest.
DASC 500 Project
Framing a Data Analytics Study Using CRISP-DM
Your assignment is to develop a data-analytics plan using the CRISP-DM framework. As
a plan it should propose or outline, as specifically as possible, the application of the CRISP-DM
framework to a “business” problem of interest. It may help to consider the assignment as:
• A proposal for key stakeholders to review and either approve or disapprove, or
• A study outline to be executed by another analyst or team of analysts.
Your report should address all of the generic tasks within the CRISP-DM framework, identified
by the bold font items in the figure below.
You are free to select a project based on your current job, an area of personal or
professional interest, or some other business problem. The key is to clearly identify a relevant
business problem that would benefit from a data analytics study
Note that your assignment is to describe or propose a data analytics study — not to
conduct or execute one. Rather than conducting a study, present the business problem that
you selected, justify the application of a data analytics study, and describe the application of
the CRSIP-DM framework to that study.
While the assignment consists of three distinct submissions, the final report should
include an executive summary of no more than one page, an introduction, a conclusion, and six
primary paragraphs that follow the six CRISP-DM steps. You may also include subparagraphs as
appropriate for the generic tasks under each CRISP-DM step.
There is no minimum or maximum page limit, but there are adverse consequences, as
you know, for presentations that are either too sketchy or too verbose. An important skill for a
data analyst is to present compelling proposals as succinctly as possible. Not counting
appendices or attachments, final project reports with less than five or six pages, run the risk of
being too sketchy, while those over 15 or so pages may be too verbose.
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