We are currently developing GGViz, an advanced data visualization web app that makes it easy for people who work with big data to create multi-layer, multi-plot, multi-panel (facetted), interactive, and possibly animated graphics, in order to make data-driven decisions using big data sets and machine learning algorithms.

GGViz will empower our customers to create new kinds of data visualizations that are difficult or impossible to create using existing commercial software (PowerBI/Tableau). The insights our customers get from their big data will translate into more informed decision making, and increased value for their business.

GGViz is currently in development, and we will soon be inviting users to alpha test the web app. GGViz will offer free use for public data, and affordable monthly subscriptions for private data.

Advantages over other software

More user-friendly than open-source data viz libraries

GGViz is based on Wilkinson’s Grammar of Graphics, like the popular ggplot2 in R, and plotnine in python. But unlike those open-source tools, which are limited to producing static graphics using a programmatic interface, GGViz will provide an easy-to-use, point-and-click interface, and will produce advanced interactive graphics. GGViz is a commercial-scale re-write of our open-source prototype, animint2, which we described in our peer-reviewed research paper, Extending ggplot2 for Linked and Animated Web Graphics, published in Journal of Computational and Graphical Statistics (2019).

More flexible and interactive than commercial software

Commercial software such as PowerBI and Tableau are inherently limited to pre-defined chart types, with specific types of interaction and multi-panel display. In contrast, GGViz users can define a much larger variety of data visualizations, using our powerful interactive grammar of graphics. To see the variety of different designs which are possible, check out the animint-gallery and animint2 gallery, which contain 50+ advanced examples which were produced using our open-source prototype, animint2.