- Sign In
- Sign Up
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
Adding Dynamic Content to a Static Web Page
Just Binge-Listened to 95 SaaStr Podcasts, Here's What I Learned
Thoughts on the Data Ecosystem
The Flex.io Blog
In an excellent post, CIO Isaac Sacolick asks, what technologies work best for decentralized data scientists?
I recently found an article discussing the four different types of Data Scientists. Turns out there’s a quite a bit of wiggle in what the term “Data Scientist” might mean – from business savant to data viz wiz to world class coder to Ph.D. in statistics. A question is posed:
Recently, we’ve been seeing a lot of news about the promise of emerging applications for machine vision.
Much of it’s at the trial stage at this point, particularly with Google Glass and related projects. For instance, the police in Dubai are testing facial recognition on the streets, ER doctors are exploring uses for quick access to critical medical records and Walgreens is experimenting with augmented reality in stores.
It seems that implementing stronger security standards is not without risk. As the New York Times recently noted, Apple’s move to add full disk encryption to iOS 8 and remove any built-in backdoors has not won kudos from the N.S.A. and F.B.I.: