Ahead of his presentation at the Data Visualization Summit in Boston on September 8 & 9, we spoke to Chi-Yi Kuan, Director of Business Analytics at LinkedIn about his thoughts on the current challenges and opportunities within data visualization.
Chi-Yi Kuan has over 15 years of extensive experience in applying state-of-the-art big data analytics & solutions, data science, global risk & fraud management, and marketing effectiveness across various business domains to solve challenging large-scale problems in corporate and startup settings. He holds a M.S in Statistics and a M.S in Engineering-Economic Systems & Operations Research from Stanford University.
Innovation Enterprise: Do you think that the increased use of data visualizations in everyday life has made it possible to make them more complex than before?
Chi-Yi Kuan: The short answer is yes. In the past, data viz task is very likely handled by a small group of data experts due to limited technology. Nowadays, there are many visualization tools available for every user to get the data they want, but the issues around data quality, governance or source of truth may rise due to lack of good design of data analytics framework or process. It’s also important to have data analytics professional’s help on data interpretation and conclusion.
What do you think makes an effective visualization?
An effective visualization should help users to use the right data with very minimal barrier to visually answer a specific question. In the age of big data, there are mountains of data in every company. If you don’t have effective visualization, it won’t yield a grain of insights and returns.
An effective visualization should combine both art and science. For art, not just having a creative mindset for your visualization, but also keeping your design in a style of neat and simple to show those patterns or relationships in the data. For science, it is not just to develop various types of charts, but also make complex data more understandable for the fact of the past and the prediction of the future.
What do you think has been the biggest single development in terms of how we visualize data in the past 5 years?
The data democratization mindset. In the past 5 years, information technology has significantly enabled data to be available to everyone in most companies, large and small. As a result, data democratization provides businesses and consumers to make data-driven and informed decisions.
How do you think data viz will change in the next 5 years?
I think there will be big advances in data viz for effortless and easy to discover thanks to the information technology revolution, which enabled many players and startups to invest and innovate many disruptive tools in the past few years. More exciting advancements will be expected too, including:
- Supporting big data 3 Vs at scale: like 100X for Volume, 10X for Velocity, 5X for Variety
- The end-to-end set up time will be much shorter, the learning curve to be a data viz expert would be within days
- More flexible user interfaces with easier ways to surface complicated cases w/o any further advanced coding for discovering the underlying knowledge and relationships, such as social graphing, 3+ dimensional graphing, etc.
- More integration could happen here, such as new intelligent features in data viz application for predictive modeling, pattern discovery, automatic alerting, etc.
- Given the recent crazy popularity in AR technology for Pokemon Go, interesting data viz application to support AR or VR will soon become available and have the potential to be a hot topic down the road.
How important do you think data viz is when communicating complex data to non-data literate people?
As an English idiom, 'A picture is worth a thousand words', Or according to Wiki on Data visualization , 'data visualization is viewed by many disciplines as a modern equivalent of visual communications'. So, it’s super important and effective to leverage data viz when communicating complex data to anyone, regardless of if they are data experts or non-data literate people.
You can catch Chi-Yi Kuan's presentation at the Data Visualization Summit in Boston on September 8 & 9.