Google Cloud Platform Webinars. So You Want a (Visualization) Ph.D.? – Multiple Views: Visualization Research Explained. One of the best ways to get involved in visualization research is to get a Ph.D. In this post, I outline reasons for pursuing a Ph.D., what you should expect from the program, and how to apply. Throughout this post, I try to view these questions through the lens of visualization. In a way, I’m a poor choice for writing a guide on getting a Ph.D., because I more or less stumbled into pursuing my own Ph.D. in the first place. All through my undergraduate years, I was convinced I would become a game developer, and it was only in the last semester when some freelance work soured that I started thinking seriously about whether I actually wanted to write code for a living.
Then, out of the blue, one of my professors sent an email encouraging me to apply to my university’s Ph.D. program. With that out of the way, let me return to the original question of this post: So you want to get a Ph.D. in visualization? But let me first take a step back. Why get a Ph.D.? But how? Why, you ask? Conclusion. What is visualization research? What should it be? – Multiple Views: Visualization Research Explained. When you hear the term “visualization research,” what comes to mind? Many people think of Tufte when they think about deep reflection on visualization. For example, ask any visualization researcher how many times their description of what they do has been met with a comment about how great Tufte’s books are.
We agree, Tufte’s books are great resources! His guidelines, like maximizing the data-ink ratio or avoiding chart junk, are helpful maxims when you are starting to design a visualization and become aware of the large space of possibilities, even to show a simple data set. Yet Tufte’s suggestions can break down in many realistic design scenarios.
Have you ever tried to follow Tufte’s advice to a T? You might end up with something like the “ghost” chart to the right. What does visualization research actually cover? Understanding of the limits of different principles and guidelines for creating effective visualizations is one goal of visualization research. Teaching Data Visualization to Kids. Think of all the things you learned in elementary school: How to read. How to write. How to count. How to do add, subtract, multiply, and divide. These are all learned skills, things that we are not innately born knowing how to do. Just like these, reading graphs is a skill. We might be taught how to read line, bar, and pie charts in elementary school because they have been around longer than others and are used the most.
But there is a wide array of graph types outside of these standard types that we can use to visualize data. My hope is that we can help people can expand their graphic literacy so that the next time they open their newspaper or open their favorite tool to create a graph, they don’t feel bound by the graph types in the default menus. Last week, I was offered the opportunity to work with my youngest workshop attendees when I visited my son’s 4th-grade classroom. I approached the class with three goals in mind: First, I wanted to show them different graphs. Draw something. Dump the PowerPoints and do data properly — or lose money. Experimental feature or Give us your feedback Thank you for your feedback.
What do you think? An unknown intruder breaks into your organisation and steals work that took your entire workforce more than 20 days to produce. Next year the same thing happens. And the next. The cumulative toll of the break-ins affects everyone in the company, sending morale plummeting. This dystopian whodunnit is no fictional nightmare: based on an annual survey of more than 30,000 employees in 167 UK companies, the “thefts” are the average number of annual working days per worker lost to absenteeism or presenteeism (when employees come to work but are not productive). That the trend is worsening suggests that not enough company boards are acting on this intelligence, perhaps because it somehow seems less real than a one-off physical break-in. So what can data analysts in organisations do to get their messages heard?
But there are techniques that can be used to encourage progressive change in the boardroom. The Rise of the Data Engineer – Maxime Beauchemin – Medium. I joined Facebook in 2011 as a business intelligence engineer and by the time I left in 2013, I was a data engineer. I was not promoted or assigned a new role, we simply came to realize that the work we were doing was transcending classic business intelligence and that the role we had created for ourselves was a new discipline.
As my team was at forefront of this transformation, we were developing new skills, new ways of doing things, new tools, and more often than not turning my back to traditional methods. We were pioneers. We were data engineers! Data Engineering? While the data science discipline was going through its adolescence, self-affirming and defining itself, data engineering was the slightly younger sibling going through something similar.
Like data scientists, data engineers write code, are highly analytical and are interested in data visualization. ETL is changing We’ve also observed a general shift away from drag-and-drop ETL tools towards a more programmatic approach.
Tau Day | No, really, pi is wrong: The Tau Manifesto by Michael Hartl. Papers. Ethics. Most liked Data & Analytics - SlideShare. Tutorials. Labs. Courses. The Rise of Data-Driven Decision Making Is Real but Uneven. Connecting with the Dots - on data visualization, empathy, and representing people with dots. Dots or people—what do you want your readers to think? (Ryan Norton via Flickr.) Jake Harris on data visualization, empathy, and representing people with dots One of my favorite movies is the classic 1949 thriller “The Third Man.”
The story is about a writer who arrives in gloomy post-war Vienna on the promise of a job only to instead unravel a criminal conspiracy to peddle diluted—and thus ineffective—antibiotics. In a pivotal scene during a clandestine meeting on the top of a Ferris wheel, the hero confronts a duplicitous friend about his lack of conscience and angrily asks if he has ever seen one of the victims of the tainted medicine he sells. Mr. Duplicity offers this cynical reply while looking down on the amusement park below: You know, I never feel comfortable on these sort of things. From a distance, it’s easy to forget the dots are people. Ultimately, I think the graphic produced by the Times did an excellent job of reminding readers about the human costs of the violence.
Big Data 101: Data Visualization For All | Centric Digital. As companies try to make sense of the vast amounts of data they’ve collected, data visualization becomes crucial. The contextualization and execution of this information is really where the money is—but how do you get started? Change is a challenge for any company, but the businesses who adapt are the ones who tend to thrive. One of the major changes companies are faced with today is the vast amounts of data available at their fingertips and the insights all this information can provide. While businesses know this data is a gold mine, many are having trouble finding strategic ways to sift through so much information and present it in an impactful way.
Enter data visualization. This is no longer an approach reserved for digital companies like Facebook or Google—big data visualization is a strategic approach that is tremendously helpful for all companies in capturing the proper insights to make sound business decisions. Four elements to displaying data What to avoid Approaches to consider.