Data Visualization and Business Intelligence Newsletter
Source: lisacharlotterost.github.io
11/23/2016Let’s map the unmapped voters. Let’s not show the winner of each state, but the percentage of people and voters that voted for a specific candidate: The popular vote. I talked and wrote about the reasons to do so. The following graphics and maps are dedicated to the popular vote of the US Election 2016 (you know, the one last week. The one where Trump won).
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.
52 different charts in flash cards. Need I say more? Here are the first of its kind flash cards for charts & graphs from PolicyViz. Use them for teaching, researching, or spurring your imagination.
In this article, we will look at how you can interactively plan for different scenarios to model the growth of your startup by working with the tool developed at Vizually Labs. Before we begin, let us look at what is Fundamental Unit of Growth (FUG) and then look at the tool below.
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.
In this technical tutorial Amanda Patist from The Information Lab explains how default hierarchy drill down behavior in Tableau can be enhanced to allow selective drill down. To implement this functionality she has parameter control and Tableau Javascript API.
Should you use stream chart, packed bubble, sunburst or a waffle chart? Avinash Kaushik looks at six examples of how different data visualizations can help explain the data better.
How the next piece of clothing you buy may be designed by computers? The team at Stitch Fix shares how they use data science to design a blouse.
Chernoff visualization symbolizes data using faces. Martin Elmer discusses how Chernoff does a poor job of communicating information and why you should avoid it.