July 30, 2018• 3 minute read
Before starting Mode, I was an analyst. It's embarrassing to admit, but at the time, I thought I had all the answers. I thought that being the one with access to data made me the arbiter of truth, and that I was right by default when talking with someone who wasn't using quantitative information to back up their ideas.
June 25, 2018• 4 minute read
Associate Marketing Manager
For many of Mode's employees, this is their first job at an analytics company. Those team members often assume that Mode's internal analytics processes mirror the way analysis is commonly conducted within other organizations. In some ways, that assumption holds true. As CEO Derek Steer puts it, "I wish I had a more mind-blowing story for how we do internal reporting... But mostly, it's funnel analysis." That said, we approach analysis from some uncommon angles.
May 30, 2018• 2 minute read
Plotly lets analysts and developers create powerful interactive visualizations, whether offline or right in your browser. Plotly.R is now available in Mode’s new R Notebooks. This means that it’s easier than ever to build all kinds of custom, interactive R-powered visualizations right into your Mode reports and dashboards.
April 25, 2018• 6 minute read
Among data scientists and analysts, R has long held its own against Python in the battle to determine the “best” analytical programming language. Statisticians and numerically-savvy academics of all stripes have typically preferred R to Python, so lots of R&D - both inside the ivory tower and in various industries - gets done in R.
April 17, 2018• 3 minute read
Four years ago, Mode set out to build the best data platform for every analyst in the world. Since then, we've seen more and more people doing analysis as a key part of their day-to-day work. Today, we're releasing two of the biggest updates in Mode's history, designed not only to make Mode more powerful, but also to make that power accessible to everyone.
April 10, 2018• 5 minute read
Data Science Evangelist
Specialized tooling has proliferated the data engineering community. This trend is growing, and the data infrastructures of modern organizations are becoming more modular. There's a bright future ahead for data engineering, one in which the tools and technology we depend on are increasingly designed with depth and cohesion in mind.