The data science team at Goji – a Boston-based automobile insurance provider – employs Python scripts to combine and analyze data from the company’s call centers, CRM, and website traffic. They then visualize and share the data with their colleagues using Plotly Enterprise and an internal website. Screens throughout Goji’s offices display Plotly dashboards that update in real time. It’s smart, clear, and easy for everyone in the office to follow.
When Goji made the decision to replace monolithic, GUI-based data analysis software with Plotly Enteprise and a suite of lightweight, automated Python scripts, the result was a data science stack that was less expensive and more flexible. And, as an added bonus, “no one at the company complains about it anymore.”
Plotly Enterprise equips teams to answer tomorrow’s questions instead of yesterday’s demo by connecting to real back-ends – R, MATLAB, and Python – that don’t limit data sources to a predefined architecture. Like other data science developers, the guys in Goji’s team now have big smiles on their faces because their work is creative, agile, and exploratory. The days of coming up with hacks to respond to issues that monolithic BI tools were not designed to sort out are long gone. You go, Goji!
For more on how Goji is using Plotly Enterprise, see these tutorials on Modern Data: