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Business Question
How does ones daily stress impact their goal participation to consume more water?
DSA-2: Data Preparation and Visualization
3. Preparing your Dataset (10 pts)
Provide a summary of how you modified your dataset with an explanation. You will use this section to document your experience. Questions to consider: how many columns did you use? How many columns did you delete? How many rows did you delete? How was the overall data quality? How many data sources did you have? During your analysis, did you have to gather more data?
Evaluation: grading you on your dataset. Was it structured? Scrubbed for quality? Did your explanation make sense?
4. Storyboard (30 pts)
In part 1 of the course (Weeks 1-5) we covered nine data mining methods (e.g., logical regression, classification). In part 2 (Weeks 6-10), we read from the Knaflic book. My intent on providing a wide range of concepts is to give you a library of methods to consider. I want to simplify the learning process by letting you explore methods that you find interesting and select the methods you are comfortable with based on your previous knowledge of math and statistics that you most likely experienced in middle school through high school. Remember, concrete experiences are important to leverage in analytics.
Your data visualization needs to produce four components (e.g., graphs) and needs to tell an overall story. You will insert your data components into a visualization (See Section 5). I would recommend using MS Excel for your tool.
To complete this section, you need to provide a brief synopsis of how you created your four components. Focus on describing your analysis. Maybe you apply some of the concepts from Knaflic and/or other materials in the course. Just specify which ones you used and describe what those methods accomplish. MS Excel also has methods for creating visualizations. You are welcome to explore those features as well.
Evaluation: grading you on your ability to apply concepts that you’ve learned in the course. You will want to consider leveraging any of the models such as descriptive, prescriptive/decision, or predictive. Additionally, you can apply any of the data mining methods such as regression or classification that we’ve covered.
Graph 1: Name
Tell me about …..
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Graph 2: Name
Tell me about …..
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Graph 3: Name
Tell me about …..
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Graph 4: Name
Tell me about …..
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5. Storytelling with Data (40 pts)
Below is an example of what a previous student built. This is an average visualization. I would note that in the Storytelling with Data book that the Knaflic does not suggest using pie charts. If you are using pie charts then I’m assuming that you didn’t read the book or take that coaching into consideration. I would not recommend using pie charts. In Week 11, I will share some of my analysis of the soccer match with you. I expect you to use Weeks 9 and 10 to do you analysis and attempt to build some visualizations in Excel. I’ve given you some resources to consider and I want to give you a chance to leverage those resources. Weeks 9-12 are designed to be a progression. Do not wait until Week 11 and 12 to do this work. Use your Revision History to show progress each week.
Provide talking points to support your visualization below:
- Talking points…
- Talking points…
- Talking points…
Evaluation: were you able to follow directions? Were you able to use MS Excel to create your four graphs? Did your presentation look compelling and professional? Did you take time to “design” how you presented your data? Did your data tell a story?
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