Brief overview of the TUN Data Challenge I conducted with a team as part of SNHU experiential learning course. We work with client, marketing, and interaction data from non-profit, Hire Heroes USA to answer business problems specified by the organization. Our process involved: Defining goals, cleaning data, exploratory data analysis, statistical analysis, data visualization, and communicating results. Final results from the contest are still pending, expected in late July.

Over the holiday season I heard several discussions on which charities are best to donate to and why some are better than others. With this in mind, I thought it would be interesting to examine the stats which set one charity over another and find a way to visualize these in an effective manner. With some help from Charity Navigator, I was able to source and collect the appropriate information and thought it a great time to finally give Plotly a go.

A few visuals I created in Tableau displaying some trends in life expectancy by country. Data was sources from the World Bank Open Data website and includes life expectancy at birth of around 200 countries from between 1968 and 2014. Originally conducted for SNHU Data Visualization homework assignment in which to express data in five different method classifications: comparison, hierarchical, temporal, correlation, and geo-spatial.

Quick dashboard I threw together in Qlikview for a school assignment. Data was a survey collection of goal opinions of 4th to 6th graders in Michigan schools. A few demographic variables are also recorded.

Another project completed during Udemy's Tableau A-Z course. This was more focused on exploration and analysis of the data provided. Cluster analysis in particular was explored and evaluated throughout.

First go at creating a dashboard in Tableau. Data used was an example dataset of customer data from a newly formed bank in the UK. The data, and the project as a whole, was done originally as part of Udemy's Tableau A-to-Z course.