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Use what you’ve learned about data visualization thus far to create a story in Tableau that explains, investigates, or makes a case for something. In your story, incorporate at least:
· A story containing at least two story points.
· At least two data sources JOINED together.
· At least one additional data source added independently, not joined to the other two.
· Some advanced interactivity (e.g. buttons, dashboard actions, etc…).
· Some calculation.
· In your story, please add an additional point at the end with text that highlights any invisible things you did to make your story better. Things like calculated variables are invisible, so please draw my attention to them here. This page does not need to be styled, plain text in point form is fine.
There are some good data sources posted on Moodle that you may use. If you want to spread your data science wings you can use almost any source that you’d like.
Good data sources include:
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· Edmonton open data (info on lots of things tracked by City of Edmonton).
· Kaggle (website with many datasets, requires free account).
· Google dataset search.
When creating your story, you want to walk the reader (me) through some aspect of your data. Typically, this will be something like going from a general view to focus in on specifics or creating story points to show changes over time. You are using the data to explain something to me, so your story should explore that.
The only thing evaluated will be the story, so anything you want graded should be in a story point.
When submitting your assignment please submit the published Tableau public link in the Moodle dropbox. Prior to publishing please hide the worksheets in your workbook, show me only the finished product – the story.
This assignment is, purposefully, open-ended. The requirements listed are a starting point, you should incorporate the concepts we’ve covered in class, along with any other techniques you have researched to create a set of visualizations that are engaging and comprehensive.
The story will be graded in two categories (plus the bonus marks):
· Completion of the required components.
· How well the components were used to craft a coherent narrative.
The mark distribution will be as follows:
· Completion Criteria:
o At least 1 story with 2 visualizations (3 marks).
o At least 2 joined data sources (2 marks).
o At least 1 non-joined data source (2 marks).
o Advanced interactivity in at least 2 places (3 marks).
o Note: All of the above are complete/incomplete, the exception is that marks may be withheld if the requirement is technically complete, but trivial in terms of value.
· Quality Judgement:
o Data join accuracy/quality/suitability (0-5 marks).
o Overall (0-10 marks).
o Note: The above are subjective judgements of the impact of the visualizations. Based on how clear, impactful, and coherent the story is at communicating your point. Creating more complex visualizations, choosing deeper topics, and creating more (good) visualizations are all good ways to make your visualization subjectively better.
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