I was always struck by how the Silicon Valley startups I worked with could do so much more, with so much less. I’ve come to learn, sometimes the hard way, that there are critical elements of the “who” and the “how,” particular to those start-up teams, that contribute to their success. It’s why we named our company for Silicon Valley: a lightweight, agile approach to data-driven product development was pioneered here.
In this post, Fausto talks about the characteristics that differentiate data infrastructure development from traditional development, and highlights key issues to look out for.
Several of our presenters were interviewed at Strata San Jose. If you missed the conference, check out these interviews below to catch up on some of the topics that were on our minds.
In this post, Richard walks you through a demo based on the Meetup.com streaming API to illustrate how to predict demand in order to adjust resource allocation.
In this post, we explain why anyone transforming their company into a data-driven organization should care about software development best practices, even if they don’t consider themselves a software company.
Here are some links from around the internet to get you in a Strata state of mind.
There is little limit to what can be done with a notebook. As well as the data science work you might expect, such as manipulating and graphing data, we’ve used them for sharing work on analytical tasks such as motion detection in video. In this post Edd takes a look at why we’re seeing notebooks everywhere.
In Fall 2014, Sanjay spoke about “Unlocking Business Opportunity from Big Data” to a group of former CEOs and senior business executives. This Throwback Thursday post shares some questions they had, and advice he gave.
In today’s business climate, executives understandably want to see both early results and a long-term direction. A data strategy helps meet business needs, while ordering work in a way that respects constraints and creates future opportunities.