GO YOUR OWN WAY
My Experience as a Freelance Data Scientist
Itching to strike out on your own? Read up on the pros and cons before you give your two weeks notice. - Greg Reda

BOOKMARK IT
Awesome visualization research
A curated list of data visualization research papers, books, blog posts, and other readings. It's pretty fresh, so submit a pull request and contribute! -
Matthew Conlen

DIVE IN
Quantifying and Visualizing “Deep Work”
In the zone. Heads down. Deep work. Whatever you call it, you know that feeling—when you're intensely focused and everything just flows. One professor analyzed a year's worth of these sessions. Productivity insights abound. - Enrico Bertini

CHARTSTORM
Visual Vocabulary
A handy reference used at the Financial Times to improve chart literacy across the newsroom. Chart types are divided into categories by data relationship (e.g. deviation, correlation, distribution), so you can get some initial ideas for which visualization might work best. - Financial Times

Q&A
Quora Session with Monica Rogati
The Former VP of Data at Jawbone did a Quora session last week. Here are a couple of especially helpful responses:

• What are the challenges of building a data team at a startup?
• What characteristics make for a good data scientist?

People are talking about: Uber Movement

Last Sunday, Uber launched Movement, “a website that uses Uber’s data to help urban planners make informed decisions about our cities.” While some city governments have been clamoring for Uber's data all along, others are questioning the move due to privacy concerns.

• Introducing Uber Movement (Uber)
• Uber Extends an Olive Branch to Local Governments: Its Data (New York Times)
• Ride-Sharing Data Will Be Available to All. Will Privacy Be Protected? (Science Friday)
• Finally, Uber Releases Data to Help Cities With Transit Planning (CityLab)

New from Mode

Beyond Clicks and Opens: Measuring the Impact of Engagement Campaigns
Right out of the box, most email marketing platforms only track vanity metrics. By using SQL to combine raw product and email data, you can better understand how email interventions might be driving desired user behavior.