Visualization in Motion: How to Create Effective Data Visualization with Real-Time Data

Is your data visualization optimized for your real-time data? Likely not. Every company needs a real-time data strategy but even when they have one, they often neglect to invest in charting solutions that can handle that data. It's easy enough to show throughput on a line chart or track offsets visually but are those the most effective methods for observing, analyzing, and diagnosing real-time data? We can do better.  

  In this session, we’ll start by taking a look at common strategies and technologies for visualizing real-time data, like line charts, time bars, and dynamic flow diagrams and where those approaches fall short. From there, we’ll switch gears and see where we can do better by showcasing some more effective forms of data visualization for your Kafka data streams within the context of their schemas and broader workflows. You’ll learn how to use traditional visualizations more effectively, see how to bring new methods like time-inflected distributions into your toolkit, and explore where you can deploy new metrics that encode properties like trajectories and anomalies for greater impact. We’ll discuss when to use more advanced chart techniques like annotations and animation (and when not to).  

  By the end of the session, you’ll be better equipped to build a view into the data that empowers users to see the entire data streaming experience, allowing them to see more patterns and make more effective decisions from their real-time data.