The "Aha" Moment: How to Onboard an API Service and Get Active Users
Introducing Serverless Data Feeds
Share Data Without Sharing Credentials: Introducing Pipe-level Permissions
How to Embed a Live, Refreshable D3.js Chart into GitHub Pages
A 90 Degree Tilt: Introducing Vertical Pipes
A Simple Pipe Routing Example: HTML Upload to HTML Display
Introducing our API and Command Line Interface: Flex.io for Developers
Just Binge-Listened to 95 SaaStr Podcasts, Here's What I Learned
About Paulo Nascimento
When asked his favorite part about interning at Flex.io, Paulo responded, “the near infinite supply of Coca-Cola and animal crackers”. He also likes looking at cool data maps and hopes to make his own map one day.
[Editors note: As a bunch of data geeks, we always enjoy getting our hands dirty exploring interesting data. This is the third of a three-part series on data sets with a story to tell; check out part one and part two. Also, you can find the source data here.]
When looking at how well NFL teams perform, we often talk about everything from offensive formations to coaching and personnel to properly inflated footballs. But what about external factors beyond a team’s control – are there ever any scenarios where the cards are stacked?
It’s easier than ever to make your own data visualizations these days. Countless new charts are being posted to the internet every day, made with a growing number of tools and openly available data sets.