September 11th, 2017 by Meg Blanchette
A leading wearable medical device company needed to understand why patients may discontinue treatment. Silicon Valley Data Science helped the client predict who would churn, and how to prevent it.
September 11th, 2017 by Jamie Bailey
The Strata Data Conference is where cutting-edge science and new business fundamentals intersect—and merge. A couple of us will be there in December, discussing data strategy and machine learning. Let us know if you’ll be attending and would like to chat.
September 8th, 2017 by Meg Blanchette
A top-five global investment management firm needed increased reliability, read/write access, and usability for risk data.
Silicon Valley Data Science designed and tested a more efficient, scalable next-generation architecture to support the needs of future data growth and business demand.
This past August was the first JupyterCon—an O’Reilly-sponsored conference around the Jupyter ecosystem, held in NYC. In this post we look at the major themes from the conference, and some top talks from each theme.
September 5th, 2017 by Meg Blanchette
A major global sportswear brand needed to understand why users were churning from their app at such a high rate and what they could do about it.
Silicon Valley Data Science developed methods to monitor patterns of customer behavior over time so that the client could make better marketing and development decisions.
August 29th, 2017 by Jamie Bailey
John Akred will be in Seattle for Data Day Seattle talking about how machine learning. Let us know if you are also attending!
You should understand whether the right things have been measured and whether the results are suitable for the business problem.
How can you manage your implementation in a way that allows you to take maximum advantage of technology innovation as you go, rather than having to freeze your view of technology to today’s state and design something that will be outdated when it launches? You must start by deciding which pieces are necessary now, and which can wait.
In this tutorial, we will walk you through some of the basics of using Kafka and Spark to ingest data.