University of Wisconsin Data Science DegreeUniversity of Wisconsin Data Science Degree

How can we help? 608-262-2011

Chat

Apply Now

Menu

  • Data Science Programs
    • Master’s Degree
      • Courses
      • Our Master’s Students
    • Graduate Certificate
      • Courses
    • Program Outcomes
    • Faculty
    • Accreditation
    • FAQs
    • Program Advisory Board
    • About UW Extended Campus
  • Get Started
    • Application & Admission
      • Master’s Degree
      • Graduate Certificate
    • Tuition & Financial Aid
    • About Online Learning
    • Technology Requirements
    • Talk to an Enrollment Adviser
  • Current Students
    • Access My Online Course
    • Registration
    • Course Schedule
    • Textbooks
    • Technical Support
    • Online Writing Lab
    • Student Services
    • Program Integrity
    • Capstone Projects
  • About Data Science
    • What Is Data Science?
    • What Is Big Data?
    • What Do Data Scientists Do?
    • Data Science Careers Outlook
    • Data Science Salaries
    • Data Science Jobs
    • News & Media
  • Experience UW Data Science

Archives for April 2016

9 Powerful Data Visualizations That Could Change Your View of the World

April 21, 2016 By Peggy Rynearson Leave a Comment

  • facebook
  • twitter
  • linkedin
  • email

“If you’re navigating a dense information jungle, coming across a beautiful graphic or a lovely data visualization—it’s a relief. It’s like coming across a clearing.”

Renowned data journalist David McCandless said this. His work will pop up several times in this post, and for good reason. His data visualizations are among the best, like candy for the eyes and the brain. (WARNING: You could kill several hours looking through his website, Information Is Beautiful.)

A great data graphic can change the way we see the world. To demonstrate how creative and investigative—as well as illuminating—data science can be, we selected nine of the most fascinating data visualizations on the web.

Get ready to gain new perspectives on everything from national spending, music, and creative routines to sports, dog breeds, and movies.

1. A Visual Comparison of Billion-Dollar Spending

Ten billion. Fifty billion. Sums this large can be difficult to conceptualize. That’s why McCandless analyzed spending and earning figures reported by the media and transformed them into simple squares set beside each other. With this data visualization, you get a sense of size of billions spent, owned, or earned.

data visualizations

2. The Most Timeless Songs

“No Diggity” is officially timeless, according to data scientists’ analysis of Spotify data. The research, which examined number of playcounts on the music-streaming site, resulted in a list of the most “timeless” songs from different decades.

At 50 million playcounts, it’s not difficult to guess the landslide musical victor of the 90s. But what about earlier eras or the most-played rap hits? Does Daft Punk’s “Get Lucky” have the potential to become timeless? It’s all here in this interactive data visualization.

data visualizations

3. Daily Routines of Famous Creative People

Who knew that Darwin laid in bed for two hours at night solving problems? Or that Kafka wrote only at night, Maya Angelou worked in nondescript hotel rooms, and Victor Hugo always followed morning writing sessions with ice baths on the roof? We do, thanks to this graphic documenting how 26 great minds structured their days.

data visualizations

4. Most Valuable Sports Franchises

This data visualization examines the value of sports teams based on three factors: number of championship wins, longevity, and monetary worth. According to the data, the most valuable team is Real Madrid. The least valuable? Oakland Raiders. Let the feuding begin.

data visualizations

5. Which Canine Is Top Dog?

Based on intelligence, longevity, ailments, and other factors, McCandless produced data scores for different dog breeds and plotted the scores against the popularity of the breeds. The resulting graph reveals overlooked treasures (the Welsh springer spaniel!) and the inexplicably overrated (the bulldog!). How did your pooch fare?

data visualizations

6. Timeline of Media-Inflamed Fears 

The Y2K scare was nothing compared to global panic over swine flu and Ebola outbreaks, as shown in McCandless’s timeline of the world’s biggest fears and how the media amplifies them.

When you dig into some of this data, things get really interesting. For example, fear of violent video games peaks every year in November and April. Why? McCandless shared his conclusion: Christmas video game releases create an upsurge in concern about the content. And in April 1999, the Columbine shooting happened, and some believe this was influenced by violent video games. Every year since, the media has reminded the public of this event in April.

data visualizations

7. Are Hollywood’s True Stories Really True?

You’re sitting in a movie theater and see “based on a true story” appear on the screen. At the data level, what does that mean? Here are ten of Hollywood’s latest and greatest “true” stories, broken down scene-by-scene and analyzed for accuracy. Based on final percentages, The Big Short stayed closest to the truth and The Imitation Game took the most liberties with its source material.

data visualizations

8. Your New Book Bucket List

McCandless pulled data from reviews, awards, and public surveys to create this consensus cloud of non-fiction books everyone agrees are worth reading. (Capote for the win!)

He also did a version featuring American fiction novels.

data visualizations

9. How to Dance to “Shout” Without Ending Up on the Floor

If you can’t immediately relate to this problem, you’ve clearly never danced at a wedding. Or you, like this data analyst, pinpointed the exact rate at which you should descend during the 17 repetitions of “a little bit softer now” of the song “Shout.”

data visualizations

The author’s rule of thumb? Take your height in feet and divide by three. That’s how many inches you should descend on every repetition. And yes, this may not change how you see the world—but it does change how the world sees you. You will thank us next time you go dancing and don’t pull a John Belushi.

shout_poor_planning

 


Interested in a data science career? Visit the UW Master of Science in Data Science homepage, download the program guide to the right, or speak with an enrollment adviser at 608-262-2011 or learn@uwex.wisconsin.edu to find out whether this online master’s program is right for you.

Read More Data Science Stories

[Webinar] View Professor Lyna Matesi’s Interview with Data Science Guru Zach Gemignani

New Video Showcases UW Data Science Online Learning Experience

Data Management: An Interview with a Career Professional

  • facebook
  • twitter
  • linkedin
  • email

Filed Under: Careers Tagged With: data visualizations

New Video Showcases UW Data Science Online Learning Experience

April 12, 2016 By Peggy Rynearson Leave a Comment

  • facebook
  • twitter
  • linkedin
  • email

Wake up. Let the dog out. Drop the kids off at school. Work from nine to six. Pick the kids up from practice. Go to the gym. Get dinner on the table. Clean up. Their schoolwork.[Your schoolwork.] Orchestrate bedtime. Sleep. Repeat.

Is earning a degree or certificate actually realistic for a fast-paced life like yours?

Yes, absolutely. No matter what your daily schedule involves.

Online learning through the University of Wisconsin Master of Science in Data Science program is convenient and flexible enough to fit even the busiest schedule. A simple Web interface makes it easy to access courses, connect with instructors and classmates, check your grades, and get support from student services when you need it. Clear course expectations help you stay on track and plan your studies around work and family life.

Watch this video to discover six reasons why you will love learning about data science online through University of Wisconsin.

If you’d like to find out more about online learning, visit the About Online Learning page of our website.

Are you looking to start or advance your career in data science? Find out why the online UW Master of Science in Data Science is a great program for aspiring and established data professionals. Call 608-262-2011 or email learn@uwex.wisconsin.edu to discuss your options with an enrollment adviser today.

  • facebook
  • twitter
  • linkedin
  • email

Filed Under: Degree Program Tagged With: video, master's

[Webinar] View Professor Lyna Matesi’s Interview with Data Science Guru Zach Gemignani

April 6, 2016 By Peggy Rynearson Leave a Comment

  • facebook
  • twitter
  • linkedin
  • email

Zach Gemignani UW Data Science webinar

Did you miss our free webinar on March 30? Worry not. You can view it here right now, or anytime!

In this 60-minute webinar, University of Wisconsin Data Science Professor Lyna Matesi interviewed Zach Gemignani, co-author of the book, Data Fluency: Empowering Your Organization with Effective Data Communication.

Zach is the co-founder and CEO of Juice Analytics, a company that helps organizations display, communicate, and act on their data in exciting and easy-to-understand ways. Zach and his brother, Chris, co-authored Data Fluency, which Dr. Matesi’s students use in her course, DS 735: Communicating About Data.

Talking About Data Science

The conversation between Professor Matesi and Zach focused on what it takes to create a data-fluent culture in any organization. Specifically:

  • What is the Data Fluency Framework, why it is useful, and what inspired it.
  • Some important lessons Zack has learned from past mistakes in producing and sharing data products.
  • How long it takes to build a data-fluent organization.
  • Ways Zach has overcome cynicism about how data is presented.
  • Which is more lucrative: taking a job as a data scientist or starting your own firm.

By all accounts, the webinar was a big success. UW Data Science Program Manager David Summers said, “This event was great. About 40 participants joined the webinar. Lyna and Zach had a good conversation and answered questions from the audience. From everything I have heard, people found it interesting and valuable. So stay tuned. We plan to offer more of these events in the future!”

View the recorded webinar now.

About Juice Analytics

Juice Analytics was founded in 2005 because brothers Zach and Chris saw a problem in the marketplace. Organizations were working hard to analyze and disseminate data, but they were not delivering the “last mile” in data visualization—where data actually creates better decisions. Juice Analytics is tackling this problem head on.

To find out more, visit:

  • About Juice Analytics: http://www.juiceanalytics.com/about-us
  • Juice Analytics LinkedIn page: https://www.linkedin.com/company/1023205
  • Free white papers and guides: http://www.juiceanalytics.com/white-papers-guides-and-more/

Are you looking to start or advance your career in data science? Find out why the online UW Master of Science in Data Science is a great program for aspiring and established data professionals. Call 608-262-2011 or email learn@uwex.wisconsin.edu to discuss your options with an enrollment adviser today.

  • facebook
  • twitter
  • linkedin
  • email

Filed Under: Degree Program Tagged With: webinar

Request Information - Data Science Programs

25-right-facingDownload an overview of the online UW Data Science programs, complete with information about courses, admission, and tuition.

This field is for validation purposes and should be left unchanged.

Pages

  • Home
  • Program Information
  • Get Started
  • FAQs
  • Experience UW Data Science
  • Site Map
  • UWEX Diversity Statement

Connect

  • twitter
  • facebook
  • youtube
  • rss

CONTACT

780 Regent Street Suite 130
Madison WI, 53715

Advising:
608-262-2011
learn@uwex.wisconsin.edu

Current students can email: datascience@uwex.wisconsin.edu

Technical Support:
1-877-724-7883

UW Extended Campus

A Collaboration of the University of Wisconsin System

University of Wisconsin System

Copyright © 2022 Board of Regents of the University of Wisconsin System. All rights reserved. | Privacy Policy | Log in