The following projects were created as a part of my completion of the Masters of Data Science and Analytics program at the University of Calgary.
The visualizations for this project are for a datastory, which you can read in full HERE. An overview of the project can be found in the video below.
With this project are descriptive visualizations I created for my Calgary Transit Visualization project. For the full analysis check out the report by clicking HERE.
A series of 5 mini-datathons created to communicate information about a variety of different types of data in one shot. These visualizations were created for a visualization course.
The objective of this project was to create a relational database and then use SQL to retrieve data. Python's Altair package was used to visualize analysis findings. To view the full Python and SQL code, click HERE.
The Data by Design Datathon was hosted by the group GeoWomen YYC. It was a datathon meant for all skill levels, all backgrounds and all genders, which made it a very welcoming environment for my first datathon. With the general theme of "Environment, Social, and Corporate Governance", I was able to use any dataset within that category. My project was focused on exploring the state of homeless in Alberta, with the goal of refining my scope at a later time.
** This Tableau slideshow is best viewed on a desktop/laptop.
The following projects were created as a part of a Data Analytics course during my Bachelor of Commerce at the University of Calgary.
The earthquake visuals were made in Tableau. To see how I created the visualizations in the slideshow and more, watch the "How I Created my Visualizations" video below!
I retrieved some book review data form the popular book reviewing website goodreads.com and then performed a few analysis tests on the data. Watch the "How I Conducted my Analysis" video below to see what I did! The R file for this project can be downloaded HERE.
For my group project, two of my classmates (Kady Chok & Kristen Drotar) and I performed visual and statistical analysis on a 2018 dataset about threatened species. Watch the video below to hear about our findings!