Being data-driven means breaking down silos within organizations, promoting communication, and being deliberate about the data you collect and use. Here are five articles that illustrate how modern organizations are tackling this challenge.
A basic mantra in statistics and data science is correlation is not causation, meaning that just because two things appear to be related to each other doesn’t mean that one causes the other. This is a lesson worth learning.
In this post, we go over some emerging themes in IoT and give you a solid place to start in understanding the ecosystem.
Here we share some further thoughts on imbalanced classes, and offer more resources.
In early December we hosted a meetup, featuring Dr. Alli Gilmore discussing topological data analysis, and Dr. Andrew Zaldivar covering practical usage of Tensorflow.
Data products are those whose core functions leverage data, be they physical products, software, or services. Edd dives deeper into building data products here.
In this post, CTO John Akred looks at the practical ingredients of managing agile data science.
Any technology is only as good as the way in which you use it.
Stories are all about relationships, and so are data. It’s not the datapoints, or the nodes, that matter—it’s the edges between them that paint the trendlines and allow us to say something about our future.