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Which contributing variables are being measured, or need to be measured, to address that challenge? Which variables matter most? What strategic needs are being served by data analysis?Discuss

1.Data set
Make an initial exploration of your chosen data set and record your overall thoughts and impressions (For example, think about questions like: What is the quality of this data? What kind of story does it suggest? look for patterns, contradictions, and possible interesting relationships) The given data is a University student responses (grades) to a discussion question/questions.
Spend some time deciding what to ask of the data and articulate the business problem or question that you will ask of the data . Be sure to explain the logic behind your framing of the question(s), from both a theoretical and a practical business sense. Implications:
Wasting of valuable staff time
Increasing Work Pressure
Inaccurate Results- Manual data entry- data error
Creation of Confusing Data
Placing Lesser Focus on Revenue Oriented Activities
Appropriate employee hiring and training
2. produce the models or visualizations
Will you remove outliers, insert values for missing variables, drop or add variables, or perform other measures?
Make and record your data quality assessments.
Conduct variable conversions and refinements, if necessary.
Record your process and any insights gleaned while preparing the data; is any of the data unusable?
3. prepared data to assemble a dashboard display
The dashboard must visually tell a story that reveals insights, describing its predictor variables and their interrelationships by means of data analytic storytelling (For instance, which variables will be the primary characters in your story? Which will be the supporting actors? What are the key conflicts or issues that create tension in the story? How will the story resolve those conflicts or tensions? How will the story end?)
4. . Data analytic dashboard presentation
Must have:
As a data-driven organization with a true analytics cultureā€¦ elaborate on this
Discuss the future of predictive modeling
quantitative methods that data, explain how to make sense of the data and analysis and argue for a particular interpretation.
exploring and analyzing the data
constructing a dashboard
writing the report.
subject to quality and relevance criteria; data manipulation must be driven by organizational strategy; models must be evaluated not only statistically, but also logically and practically, with organizational goals and industry standards in mind; the result should be specific recommendations to improve organizational efficiency or effectiveness
what challenge is being addressed in your chosen data set?
Which contributing variables are being measured, or need to be measured, to address that challenge? Which variables matter most? What strategic needs are being served by data analysis?
infer their meaning and implications.
different types of dashboards, characteristics of good dashboards, and the business value a good dashboard can offer.( 1 page)
the greatest challenge in dashboard creation is choosing effective visualization techniques for summarizing important data and representing relationships among variables.
Is there missing data? Does it seem to be at the wrong level of measurement? What kind of story does the data suggest?

5. Report must includes
Correctly use and explain common data analytics terms.
Correctly identify and describe basic data analytics methodologies.
Discuss an organization’s analytics maturity.
Identify an organizational problem or question that can be appropriately addressed by an analytics solution.
Evaluate a range of different analytical models that could be brought to bear on the problem.
Choose and defend a “best” model.
Apply the model and identify its implications.
Make a management recommendation(s) based on the model.

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