/Build-Data-Dashboards

This is the 4th project in Udacity's Business Analytics Nanodegree

MIT LicenseMIT

Project Description: Build Data Dashboards

This is the 4th project in Udacity's Business Analytics Nanodegree

Background

In this project, create visualizations to reveal insights from a data set. Create data visualizations that tell a story or highlight patterns in the data set. The work should be a reflection of the theory and practice of data visualization, such as visual encodings, design principles, and effective communication. There are 3 different data sets you can choose from:

  • Flight Delays and Cancellations
  • US Census Demographic Data
  • Youtube Data from the US

I chose the US Census Demographic Dataset for this project

Dataset: US Census Demographic Data

This data comes from a Kaggle dataset, it includes the census data for all counties in 2015. You can find the dataset in supporting materials at the bottom of this page. Required dashboards You are required to create three visualizations. Some questions you may attempt to answer include those pertaining to the following areas:

  1. Which states have the best transportation? This is a fairly subjective question, so your first job is to define what the best transportation is. Is it highest percentage of transit use? Is it lowest mean commute times? Then you need to determine how to aggregate the data from the county level to the state. Are there outlier counties affecting the data? How should you aggregate all the data from the counties to represent the state effectively? Please provide your reasoning in your report.
  2. How does income and poverty look across America? Think about how best to contrast this data to show an interesting finding. You can look across many of the different fields to show interesting findings. Do counties with more construction experience more or less poverty? Do counties near the coast experience more or less income? Remember this is all correlation and not causation so we cannot say any one thing causes it but we can report descriptive statistics.
  3. You can also come up with your own question! As you work with the data, come up with a question you're curious about and can be answered from the data. Build a dashboard or story to answer your question and lead viewers to that answer.

Requirements

  • Use the Project Rubric to review your project.
  • If you are happy with your submission, then you are ready to submit! If you see room for improvement in any category in which you do not meet specifications, keep working!
  • Your project must "Meet Specifications" in each category in order for your submission to pass.

Reminders

  • Your visualization work should use Tableau. Host your dashboards/stories on Tableau Public to makes them easily accessible.
  • Your visualization should be explanatory in nature and communicate specific results that you want to show.

Suggestions to Make Your Project Stand Out!

  • Incorporate more advanced visualization methods using Tableau. These should enhance the reader’s ability to understand the data and interact with the graphic.
  • Collect and include rich feedback such as screenshots with annotations, audio files, videos of walkthroughs, discussion forum links, or images of sketches with handwritten comments.
  • Explain the reasoning behind every initial design choice and every change you made. Reflect on the visualization development process.

Submission

Include the following files and information:

  • A PDF or Markdown report that includes the following sections:
  • Links to your dashboards or story
  • You must submit url links for each of your visuals from Tableau Public. If you need a reminder on how to save to Tableau Public, please see the next concept.
  • Summary: brief description of the visualization and the main story or findings conveyed
  • Design: explain any design choices you made including changes to the visualization after collecting feedback
  • Resources: list of Web sites, books, forums, blog posts, GitHub repositories etc that you referred to or used in this submission (Add N/A if you did not use such resources).

Result

The results and final submission can be found here

This project was completed, with final review and approval, on December 23, 2021