Slides: https://www.slideshare.net/DataStax/datastax-meaningful-user-experience-with-graph-data-chris-lacava-expero-cassandra-summit-2016 | Congratulations, your data is up and running in a graph database! This is the first step of many to unlocking the potential in your data. It’s easy to get mired in the complexities of graph technology and forget that real users, mere mortals, will need to use this information to inform mission critical tasks. To get the value out of your graph investment, you’ll need to provide an experience that enables users to explore and visualize your graph data in meaningful ways. In this talk we’ll take a hands on approach to applying user-centered strategies and leveraging the latest UI tools to rapidly create great experiences with graph data. Topics will include: Tailoring experiences to the intended audience and data Interacting with complex data shouldn’t be complicated for users. The key is to understand your users and build a solution that targets them. Zeroing in on user goals and creating a solution that targets them in a fast, lightweight and iterative way Using live data and rapid prototyping to inform your navigation, visualization selections and overall design Determining the the right visualization for the job Just because you can display almost anything doesn’t mean you should. Choosing the right visualizations to achieve specific goals is a key factor in unlocking the usefulness of graph. We’ll demonstrate how to match the right visualization against user needs. When is it appropriate to break out of the standard node view and visualize graph data in another context like a geospatial map? How do I determine the dominant dimensions to filter a node chart? What is the simplest, most efficient way to traverse time with large data sets? Do I need to visually expose the graph at all? Cutting through the clutter on choosing the right visualization tools Once you’ve got your goals set, how do you make it happen? Will it perform at scale? We’ll demonstrate example use cases with sample graph data and some of these tools to highlight practical uses.