I’m doing some form of data visualization learning for 180 days straight because I need to #JFDI. See post explaining how and why I’m doing this.
Most of my learning is happening at work now, which I will limit my discussion on because of possible propriety reasons. I still will try to write down three takeways to drill down the info. Suffice to say though, a lot more focused time now. Once I find a permanent place to live and get into a routine, I’ll start to fit in sometime before I start the workday.
Visualization Worked On or Created:
Spend afternoon at work building visuals and prototyping a dashboard, can’t talk more than that but three takeaways nonetheless:
- Multiple ways to create similar but diverging views in Tableau
- Dealing with data loads
- Understanding the need that will arise to QA after several table joins to make sure all data is still intact
Reading and Learning Data Visualization Theoretically/Critically:
Rapid-Fire Business Intelligence (from Tableau)
- Six attributes of rapid-fire business intelligence:
- Visual Discovery
- Blend Diverse Data Sets
- Real-time Collaboration
- Flexible and Secure Configuration
- Avoid dependencies on IT or other teams
- Build your systems with agnoistic architecture – don’t get trapped in certain software environments
- “In his 2006 book, Information Dashboard Design, Stephen Few wrote: “A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.” Leveraging that definition, we can define an effective marketing dashboard as one that enables marketers to visually display relevant and current campaign, customer, advertising and/or branding information needed to achieve marketing objectives (such as improve ROI, generate qualified leads, and deliver revenue). It is optimized to speed the evaluation of and reaction to current trends and statistics and to make that information and results accessible to colleagues.”
- “Core to modern dashboarding are these characteristics: objectives-focused, optimized for multiple data sources, visual, interactive, current, and accessible to its audience. So, start your planning by considering the following six best practices in creating and deploying effective marketing dashboards.”
- Choose Metrics that Matter
- Pull Data from all Sources to get the Full Picture
- Get Visual
- Make it Interactive for Collaboration
- Current and Live
- Simple to Access and Easy to Use
Udacity Data Visualization and D3.js
- Gestalt Principles of Perception http://www.slideshare.net/luisaepv/the-gestalt-laws-of-perception
- Elements that are placed close to each other iwll often be perceived as one group
- Items that look alike, with similar components or attributes, are most likely to be organised together
- Figure and Ground
- Viewers will perceive and object (figure) and a surface (ground) even in shapes that are grouped together.
- Objects will be grouped as a whole if they are co-linear, or follow a direction
- In perception, there is the tendency to complete unfinished objects. We tend to ignore gaps and complete contour lines.
- Figures are seen as their simple elements instead of complicated shapes
- Hue and saturation are very bad at denoting quantitative values, but very good at denoting categories.
- We don’t typically think that bars in a bar chart are similar simply because they are next to each other, nor do we assume slices in a pie chart are similar to each other because they are neighbors, but that’s actually what’s being conveyed.
- Red/Green hues can disproportionately affect color blind people
- Diverting color scales with varying levels of saturation could be used also let ppl who have color blindness see visualization