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.

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.

There's a fundamental change taking place in the way that organizations make decisions. For analysts and data scientists, the days of being forced to use conventional, monolithic data tools are ending. The individuals who answer the hardest questions within an organization can use the tools they choose. These tools let them investigate a problem, solve it, and move on.

Regardless of how agile your team might be, you're limited by how quickly you can provision a warehouse, build ETL pipelines, set up event tracking, and integrate an analytics tool. Doesn't this all take significant time and expertise to build?

Anytime you look for patterns in previous experiences, or make a tradeoff between one option and another, you're analyzing something. This means nearly everyone in the workforce does some sort of analysis every day, every time they make a decision.

The need for hard data to help make these decisions in the workplace gave birth to the idea of an “Analyst” as we know it.

A few weeks ago, Google announced a new feature, Dataset Search, that aims to make it easier for anyone to discover public datasets. Journalists, analysts, and data nerds will likely find Dataset Search useful: it uses metadata to help people discover different versions of a dataset and publications that reference it.