Session: Big Data on a Small Budget: Scalable Data Visualization for the Rest of Us
As large-scale data has become commonplace, developing scalable data visualizations for common data sizes is increasingly inaccessible for many teams. Typical solutions require a big team and expensive compute clusters; other solutions, like WebGL, require specialized skills that can hurt maintainability. Furthermore, commonly proposed solutions often don’t solve performance bottlenecks teams encounter in practice.
In this talk, Robert will discuss common backend, algorithmic, data transfer, and rendering bottlenecks for data visualization web apps and how to diagnose them. He will demonstrate intermediate and advanced solutions using open source technology that anyone can use, even if they don’t have the resources of a big tech company. Audience members will come away with a suite of solutions accessible to teams with a range of sizes, budgets, and skill sets. Many of these solutions also apply to other types of data-intensive applications.
