Tag: Best Practices

0.05 is an Arbitrary Cut Off: “Turning Fails into Wins”

Grace Tang, Data Scientist at Uber, presented insights, common pitfalls, and “best practices to ensure all experiments are useful” in her Strata Singapore session, “Turning Fails...

Best Practices for Managing Data Science at Scale

We recently published a practical guide for data science management intended to help current and aspiring managers learn from the challenges and successes of industry leaders....

Emotional Intelligence for Data Science Teams

We surveyed and interviewed some of our most successful customers to learn how they align their data science team with their business. The challenges involved are...

What Data Scientists Should Know About Hiring, Sharing, and Collaborating

In this post we summarize some of our most recent and favorite answers on Quora to questions from the community about hiring junior data scientists, sharing...

Principles of Collaboration in Data Science

Data science is no longer a specialization of a single person or small group. It is now a key source of competitive advantage, and as a...

Introducing the Data Science Maturity Model

Many organizations have been underwhelmed by the return on their investment in data science. This is due to a narrow focus on tools, rather than a...

The “Joel Test” for Data Science

It's the sixteenth anniversary of Joel Spolsky's "Joel Test," which he described as a "highly irresponsible, sloppy test to rate the quality of a software team."...

Reproducible Research in Computational Sciences

This guest post was written by Arnu Pretorius, a Masters student in Mathematical Statistics at the MIH Media Lab, Stellenbosch University. Arnu's research interests include machine...

Data Science Platform: What is it? Why is it Important?

As more companies recognize the need for a data science platform, more vendors are claiming they have one. Increasingly, we see companies describing their product as...

Providing Digital Provenance: from Modeling through Production

At last week's useR! R User conference, I spoke on digital provenance, the importance of reproducible research, and how Domino has solved many of the challenges...

Ugly Little Bits of the Data Science Process

This morning there was a great conversation on Twitter, kicked off by Hadley Wickham, about one of the ugly little bits of the data science process....

How Machine Learning Amplifies Inequality in Society

This talk took place at the Domino Data Science Pop-up in Austin, TX on April 13, 2016 In this talk, Mike Williams, Research Engineer at Fast...

Uber and the Need for a Data Science Platform

For those wondering if data science platforms are really a thing, there’s a great article by Kevin Novak, the head of Uber’s Data Science Platform team....