Lindy Ryan

Based in the greater New York City area, Lindy Ryan researches and teaches business analytics and data communication at a major East Coast university. An active academic and industry researcher, Ryan's research interests focus primarily on how to use data visualization and visual storytelling to effectively and meaningfully communicate data-driven business insights. She was previously research director for Radiant Advisors' Data Discovery and Visualization practice and led research and analyst activities for the company.  She is a prolific researcher, author, and speaker at industry and academic conferences worldwide, and is the author of “The Visual Imperative: Creating a Culture of Visual Discovery.”  Follow her on Twitter @lindy_ryan


Articles by Lindy Ryan

When it comes to visualizing data, there is no shortage of charts and graphs to choose from. From traditional graphs to innovative hand-coded visualizations, there is a continuum of visualizations ready to translate data from numbers into meaning using shapes, colors, and other visual cues. However, each visualization type is intended to show different types of data in specific ways to best represent its insight. Let's look at five of the most common visualization types to help you choose the right chart for your da

Posted September 20, 2017

Organizations are embracing data visualization as more than a tool to "see" trends and patterns in data but as a pathway to a dynamic culture of visual data discovery. As with any type of cultural shift, there are going to be a few bumps along the road as innovative ways to transform data into actionable insights through the power of data visualization are sought.However, with a few considerations kept top-of-mind in the early stages of data visualization adoption, common problems can be avoided.

Posted May 15, 2017

By now we are all in agreement: The business of data is changing. Business users are more empowered to work with data; IT is becoming less about control and more about enablement. New data science job descriptions—such as the data scientist—are springing up as companies everywhere look for the right people with the right skill sets to squeeze more value from their data. Data itself is getting bigger, hardware more economical, and analytical software more "self-service." We've embraced the paradigm shift from traditional BI to iterative data discovery. It's a new era.

Posted April 07, 2017

The definition of "data visualization" often varies depending on whom you ask. For some, it's a process of visually transforming data for exploration or analysis. For others, it's a tool to share analytical insights or invite discovery.

Posted November 15, 2016

Using data visualization to support visual data storytelling is a craft, and one that takes practice, expertise, and a good bit of drafting and rewriting. Strong visual narratives that make data easier to understand, according to The Economist, "meld the skills of computer science, statistics, artistic design, and storytelling."

Posted June 07, 2016

Thanks to the digital business transformation, the world around us is changing—and quickly—to a very consumer- and data-centric economy, where companies must transform to remain competitive and survive. The upshot is that for many companies today, it is a full-on Darwinian experience of survival of the fittest.

Posted April 08, 2016

As data visualization increasingly becomes top-of-mind for data-driven organizations, it's time to introduce the concept of data visualization competency. There is a need today to provide a framework to fingerprint data visualizations as unique digital assets in the business for maximum impact and consistent execution against strategic business practices and goals.

Posted April 01, 2016

Not too long ago, large volumes of information were available only to the select few organizations able to afford the expensive IT infrastructure to collect, store, manage, and analyze it—the big-budget companies with seemingly bottomless pockets, or the professional research services that built empires on collecting and interpreting data. But now, through the realized effects of Moore's law, along with the consumerization of BI tools, this data is increasingly available to everyone—and without having to dig deep into budgets or employ robust IT departments.

Posted November 13, 2015

Data-driven companies continue to explore data management technologies that better unify operational, analytical, and other disparate or siloed data in a way that offers tangible business value and data management relief.

Posted May 19, 2015

The role of friction in data discovery is much akin to that minimalist design mantra: Less is more.

Posted April 08, 2015

Companies use data—big or not—to solve business problems. The data-centric company, however, doesn't just treat data as an asset—it treats data as gold—and they're willing to pay for it, too.

Posted April 04, 2014