In this post, we will explore some aspects of the train delay data we’ve been collecting from the Caltrain API over the past few months. The goal is to get our heads into the data before setting off on building a prediction model.
It’s easy to become overwhelmed when it comes time to choose a data format. In this post Silvia gives you a framework for approaching this choice, and provide some example use cases.
We know what it’s like to deal with complex production deployments that cover the gamut from infrastructure upgrades, to feature deployments, to data migrations, where each step threatens to derail the plan. In this post she’ll give an overview of obstacles she’s faced (you may be able to relate) and talk about solutions to overcome these obstacles.
Building or rebuilding a data platform can be a daunting task, as most questions that need to be asked have open-ended answers. This post aims to help.
The role of the Chief Data Officer (CDO) continues to gain attention and proliferate as more companies hire them, and others wonder with increasing anxiety whether they should, too. The promise of data and the business value it can unlock is tantalizing, but also somewhat confusing to many organizations — the role of the CDO is, too.
The Ethereum network is a distributed economy like Bitcoin, except it is much, much more powerful. Rick Seeger dives into why you should be paying attention to its popularity.
Since launching Silicon Valley Data Science, we hear three issues more often than anything else in the conversations we have with our clients: handling data overload, choosing analytic approaches, and having the right skills and resources. Let’s take a look at these.
Andrew gives you a deep dive into pivoting data with SparkSQL. This piece was originally posted on the Databricks blog.
Parts 1 through 3 of this series looked at our preferred scenarios and best practices for instant messaging, video conferencing, and phone meetings. This final installment focuses on email.