EmpowerHer - Climate Change + Vulnerable Populations

[#1]

Team Name	EmpowerHer
Track	Student
Use Case	Analyzing the impact of climate change on economically vulnerable populations in the U.S. through data visualization and analysis.
Technology	Python, JavaScript, HTML, CSS, Node.js, SQL, and Alteryx for data analysis, web development, and creating an interactive dashboard.
Region	APAC
Team lead	Ngoi Wan Ting
Team members	@YiRong29  @Winn2509 @Janelle11
Social media handles	@yi.rong_2005 @winn_2509 @j.anelle._ @wan._.ting_
Is your team interested in participating in an interview?	N
Optional: Expand on your technology expertise	Our team has expertise in Python for data analysis, SQL for database management, and Alteryx for workflow automation. Additionally, we use JavaScript, HTML, CSS, and Node.js for web development to build interactive dashboards.

Pitch Video

Jury Video

Message from Team Lead:
We are a group of students participating in this competition to learn through the experience. Rather than focusing solely on whether we win or lose, we hope to receive feedback that will help us learn from our mistakes and improve. As we are new to SAS, we would appreciate any guidance you can provide via email to help us enhance our skills.

[LGroves]

Very nice start, @EmpowerHer!  I like how much you thought about the challenges of climate change, particularly as it relates to vulnerable populations in the U.S.  Moreover, I love that you're new to SAS and looking to enhance your analytical skills!

Since you asked, I'll share a couple of suggestions for next time.  (1) Geographic maps are a wonderful way to share a lot of data quickly... and to make it more accessible to your audience.  I recommend that you learn how to enhance your storytelling with GeoMaps... as a picture is truly worth a thousand words.  (2) Check the underlying aggregations for your variables, particularly in the Unemployment Rate by State estimate.  Unemployment rates will be bound between 0 and 100%... and it looks like the variables are simply aggregated (and thus, larger states will likely have higher cumulative rates... because there are more values to add up).  

Our SAS Visual Analytics 1 course covers both of those topics, and more, if you're like to keep learning.  You can access it via the SAS Skill Builder for Students or the SAS Hackathon Enablement Portal.  Either way, nice work!!!