I recently worked on two projects where the client wanted to show multiple metrics sliced by the same categorical data. For example, seeing how various metrics are performing over different…

When Personalize Visuals is too personalized: an experiment in switching displayed charts using a dimension attribute.

Show full category text on Y-axis of a bar chart in Power BI

I was listening to Cole Nussbaumer Knaflic interviewing Steven Franconeri a few days ago (excellent episode!) and I was struck by something they mentioned towards the end regarding the illusion of being neutral when visualizing data. Many seem reticent to editorialize their data visualizations for fear of being perceived as biased. Cole was mentioning strategies she advocates for that bring more clarity and focus but necessarily leads to more direct steering of the reader’s attention from the visualization designer’s side (highlighting, annotations, simplification, etc.)

Many managers are uncomfortable with interpreting the numbers in their reports and dashboards. If this common data literacy problem isn't addressed across management levels, companies will continue to struggle in their efforts to develop data-driven cultures. In this article, I cover four key areas of data interpretation that are essential for all managers who are striving to make data-informed decisions.

A good way to think of data visualization (data viz) is that it can be the difference between utter confusion and really grasping an issue.

In today's data economy, the word 'insight' is used frequently in business. However, in many cases, it is misused without a clear understanding what the word means. We need to enhance insight literacy, which starts with developing a clearer definition of what insights really are.

According to a NewVantage Partners survey, 99% of firms have invested in data initiatives and 92% reported the pace of investment is accelerating. However, only 24% reported having a data-driven organization. This article looks at 10 reasons why your company may not have achieved this goal yet.

To become an effective data storyteller, you must shift your mindset from being reporting centered to embracing a different storytelling approach. In this article, I introduce the Insight Funnel and how reports/dashboards complement data stories. Then I explore the six key approach differences between reports/dashboards and data stories.

Forrester reports 74% of firms say they want to be “data-driven,” but only 29% are actually successful at connecting analytics to action. Actionable insights are the missing link for companies that want to drive business outcomes from their data. This article defines six key attributes that make insights truly actionable.

The most common way of sharing data with employees has been through dashboards and reports, but they mainly focus on the 'what.' What executives really crave is the 'why'--interpreting the numbers to help inform decisions. A recent survey reveals how data stories can address this crucial need.

Data literacy is a key focus of many organizations as they seek to help their employees take full advantage of their data. While data storytelling is often included in data literacy training, the question is whether it is a required skill to be data literate. In this article, I explore the minimum viable skills someone needs to qualify as being data literate. I then share where data storytelling fits in the data literacy landscape.

Today, more and more people realize there is more to data storytelling than just data visualization. If you were to evaluate what makes a data story "good," you'd discover one crucial ingredient that's necessary--a meaningful insight. In this article, I review what insights are and the critical role they play in data stories. I also share thoughts from a recent journal article by Sorin Adam Matei and Lucas Hunter on the importance of insights to data storytelling in science communication and data journalism.

What do German Telekom, Credit Suisse, Swiss Post, German Armed Forces, and SAP have in common? They are all following the seven HICHERT®SUCCESS Rules in their financial reports. In Part 1 of this blog,

Should Ph.D. students focus more on building software people will use?

In my last post I lamented the fact that there is too little focus on data thinking in data science and data visualization, and I described how much of a struggle it’s been for me to figure out how to learn and teach these skills. When I teach my academic visualization course, the thing the most exemplifies this need is the way I struggle to teach how to formulate good

Visualization social media has been busy mocking the following char t by the Georgia Department of Public Health. Pay attention to its horiz...

A central concept in information visualization research and practice is the notion of visual variable effectiveness, or the perceptual precision at which values are decoded given visual channels...

Learn how you can set the same color for the same data value across multiple visuals and pages in a Power BI report using examples.

A guide to making visualizations that accurately reflect the data, tell a story, and look professional.

easily compare different categories on the same axes

Create Power BI custom visuals with PBIVizEditBuild your Power BI custom visuals easily under 15 minutes with mouse clicks without any coding. Only pay for visuals when you are satisfied with the …

PureViz Infographic custom visual allows turning your creative ideas into super-fast & animated Power BI visuals. Start from Power Point and bring your data to life!

This article explains how to set up your environment so that you can develop a Power BI visual.

An Open Source collection of Design Principles and methods

Choose your favorite colors and get your Material Design palette generated and downloadable.

I am a fan of the viridis color palettes available in python and R, so I decided to make Power BI theme files for each of the 4 color maps (viridis, inferno, magma, plasma). These color palettes ar…

A useful way to think more holistically about how data visualization works

Adobe Illustrator has been a tool in my dashboard design kit for quite a while. I’ve used it predominately for creating report assets such as icons, headers and backgrounds. I’ve also used it to create SVG visual elements such as the dice, turbine and scatter plot shapes and markers pictured below. But there’s another way… Continue reading Power BI + Adobe = Magic