Background
This week, we began to familiarize ourselves with the common steps associated with data cleanup. Often, the principle challenge in beginning analytic work is the difficulty in breaking down the steps necessary to achieve a desired end-goal. Over time, patterns begin to emerge and your natural speed at cleaning up data will begin to accelerate. The key is to continue honing this pattern recognition.
Your Task
In this assignment, you will play the role of Analyst for a well-known venture capital firm. The firm is currently investigating investment patterns across the United States — and is particularly interested in understanding whether certain regions behave differently with regard to Multi-Series Funding. The firm is particularly curious to understand whether companies based in large metropolitan cities outside the Bay Area see smaller rounds following their Series A.
You've been provided a dataset from Crunchbase with investment information related to companies across the globe. Your task is to clean the data such that you can quickly produce a Tableau visualizer that meets your firm's objective.
Part I: Sample Explorer
The firm has provided you with two screenshots as samples of what it's looking to re-produce. Take a few moments to study the samples to understand the end-goal.
Graph showing, by regional hub, the average total raised through series funding
Graph showing, by regional hub, the average total raised through series funding
In addition to these screenshots, the firm has provided this information:
The final visuals involve stacked bar charts. The stacks display the Average Funding by Investment Round for each of the regions. (i.e. According to Sample #2: Boston Startups in Cloud Computing raised an average of $9.3M in Round B Funding).
The final graphs filter out all companies that did NOT raise at least a Round B.
The final graphs filter out all companies not based in the United States.
The final Tableau workbook should involve NO custom calculated fields.
The final Tableau workbook should involve NO filtering other than Category in the workbook itself. All data should be pre-filtered in the CSV file.
Part II: Data Prep
Begin by opening the starter file provided. Investigate the fields to get a sense of the data fields included. Then proceed to create a workflow in Tableau Prep that generates the necessary data file to power and build your target visualization.
At minimum, your workflow will need do each of the following:
Removes any and all fields not necessary to the final visualization.
Assigns each company's category to be the first category in its category list.
Removes all Non-US based companies from the dataset.
Assigns all regions as being one of the following: SF Bay Area, New York City, Los Angeles, Boston, Austin, Seattle, or Other.
Removes all companies that have not raised at least a Round B.
Part III: Visualization Prep
Once you've generated your target visualization, re-create the visualization provided. Note, again, that your Tableau Workbook should not include any calculated fields or filters other than for Category.
Using your visualizer, capture screenshots of the hub patterns for each of the below categories:
Advertising
Biotechnology
Big Data
E-Commerce
Finance
Real Estate
Video Streaming
Part IV: Reporting
Generate a report that includes:
Your visualization screenshots
A screenshot of your workflow with 250 words of commentary summarizing the cleanup steps you took
A 250-500 word reflection on any observations you gleaned around investment patterns across the various hubs.
Your homework submission should include your Tableau Prep workflow file (.tlfx), cleaned CSV file, packaged Tableau workbook, and report file.
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