Our data doesn’t always look nice and clean. Mode's Data Scientist, Nate Coleman, shows us how visualizing distributions can tell us if our data is skewed or not—and how logarithmic scales can clarify it for us when it is.

Here at Mode, we’ve recently started building a design system to support our organization. Design systems have been a hot topic of discussion for the past few years.

Since its inception, Mode has been for data scientists and analysts. As former data scientists, my cofounders and I started Mode with the intention of building the product we wanted for ourselves. The vision expanded, but the analyst-first philosophy remained. “By analysts, for analysts” became Mode’s informal tagline.

As an analytics platform, Mode operates in a very contentious space with respect to data protection and privacy. In fact, data analytics and privacy are often viewed in conflict with each other. But are they necessarily at odds? Can you not have your cake and eat it too? At Mode, we believe you can.

Here are some quick notes on how to accelerate your data science efforts for a larger impact.

Lars Kamp is the Co-Founder & Chief Data Engineer at intermix.io where he helps customers optimize Amazon Redshift and their analytics queries for peak performance. We’ve invited intermix.io to share a guest piece detailing the new data stack.