Actionable insights define a successful enterprise, where those who can tap into the power of their data can drive new business opportunities. Mingo Sanchez, senior sales engineer, Plotly, joined DBTA’s webinar, Empowering Data Analysts and Database Professionals: Harnessing Dash Enterprise for Smarter Insights, to explore how Plotly AI in Dash Enterprise can enable actionable insights through powerful data visualization and analysis field by AI tech.
“What Plotly allows you to do is create interactive data visualizations using just a little bit of code,” explained Sanchez, in which many analysts use their familiar coding language, Python. Yet Ploty users have moved beyond analytics into more business-centered implementations.
“The vast majority of our users are starting off in simple Python scripts,” said Sanchez. “But what we often find is that once you start to build these really important, crucial applications for the business, you need some way to scale them, put security in front of them, and host them in a way that other people can access them.”
With Plotly Dash Enterprise, Ploty provides a centralized place for developers to create new apps and share them with other people. Dash Enterprise also offers infrastructural support for scaling and scheduling tasks, as well as capabilities to develop and iterate code, acting as “a very, very broad framework that lets you do a lot of different things,” noted Sanchez.
For analysts and data scientists, Sanchez demoed Plotly’s open source graphing library for Python, which provides access to a plethora of different visualizations that can be easily built with Plotly. These visualizations “are not just images on a screen,” but dynamic, easily configurable representations that allow consumers to drill-down into the underlying data.
“Anything you can do in Python code, you’ll be able to incorporate it in that [Dash] application,” explained Sanchez.
Dash, as a framework for building data applications with Python, enables you to not only view data, but act on it. Transcending beyond basic analytics, Dash allows users to directly interact with data within the visualization context—triggering whatever code the developer has written in the back-end, or callback functions.
“You can very easily write a function that says, ‘Take this information that Mingo entered, turn it into a record or request of some sort, and send that request downstream,’” Sanchez noted.
These callback functions enable developers to define triggers or user interactions that allow code to be run, what that code explicitly is, and what gets updated because of that function call. And, as Sanchez explained, “These callback functions aren’t just limited to simple operations; you can use them to build an entire report, if you wanted to.”
“You’re not just viewing analytics…you’re able to do real complex and sophisticated things with these applications,” emphasized Sanchez. “Think of Dash as just that tool to build the front-end, and you can run whatever Python code you want in the back-end. You can run a model, make an API call out to an external system, write an email—all sorts of different things.”
This is only a snippet of the full Empowering Data Analysts and Database Professionals: Harnessing Dash Enterprise for Smarter Insights webinar. For the full webinar, featuring more detailed explanations, example applications, a Q&A, and more, you can view an archived version of the webinar here.