7/11/2016How do we read pie charts? Do they differ from the even more reviled donut charts? What about common pie chart designs like exploded pies? In two papers to be presented at EuroVis next week, Drew Skau and I show that the common wisdom about how we read these charts (by angle) is almost certainly wrong, and that things are much more complicated than we thought. Pie charts are generally looked down on in visualization, and many people pride themselves on saying mean things about them and the people who use them. This is not a new phenomenon, either. Yet they are incredibly common in business settings and information graphics. The main reason for these papers was the question: do we even know how we read these charts? Is it actually angle, as is usually claimed, or is it really arc length or maybe area? It turns out that there is no actual research to back up the claims that it’s angle. The only paper we could find, and which gets cited over and over again, is from 1926. That’s ninety years ago. And the author just asked people what they thought they used, which is quite unreliable.
Few weeks ago, I came across Rocketgraph. This is a new platform that offers custom reports based on cloud data sources. While the concept is not new, what sets this company apart is the reports & dashboards are sold to users in a marketplace. The platform brings the analytics buyers and sellers together and provides the infrastructure. For years, many vendors have promised custom out-of-the-box solutions. In a majority of cases, most businesses require significant customizations. Will a marketplace approach to analytics offer an intermediate solution with significant time & cost savings? I interviewed Rocketgraph co-founder Constantine Nikitiadis to found out. Take a listen.
Data visualization blogosphere is filled with great ideas and inspiration. What is missing is the candid conversations about the limitations of data. Unfortunately, finding quality content on this topic is like finding a needle in a haystack. So, when one of the greatest thought leaders in SaaS data world wrote on this topic, I feel obligated to share it with you. Here is Tomasz Tunguz on the limitations of data.
Self-service has been a buzzword in the analytics industry for the last few years. While the self-service movement has been instrumental in bringing about rapid decision making and empowering business users get answers to their data questions, one has to be aware of the key skills still required. Stephen Few highlights this important foundation of building a data-driven culture.
Subscribing to email newsletters written by experts on growth and analytics is a great way to learn. Here are five newsletters that stand out from the rest. Written by entrepreneurs, data scientists, growth marketers and venture capitalists, each one offers unique insight into the process of using data to make better decisions and build a better company.