DareData Blog

In this post, we'll check how we can work with geographical data using Python.

To make sure your ML strategy doesn't wreak havoc on your brand, data and business teams should be more concerned with the "why" rather than the "how".

A simplified version of the conventional hiring process looks like this:

Understand the difference between correlation and causation and know how to integrate data decisions into your business

If you are a business person wondering why you should invest in DevOps / MLOps, this is your guide in terms of real live money. We'll try to keep this as non-technical as possible.

DareData is growing with no external investment, no debt, and no hype, while able to work with the best data scientists and data engineers out there. Here, I explain what we think is the root cause of our success, and what is the company set up for 2021.

There are multiple opinions regarding the usage of algorithms in business and they range from:

When we think of sales forecasting, a couple of interesting questions unfold:

So here's the deal at the time of this writing: we've got a newly created sales team that is starting to fill up our newly created sales funnel.

Update: This post was updated in August of 2022 to more accurately reflect the changes our business has undergone as we grow and adapt....

How can businesses adapt their sales forecast in times of COVID-19? In this post we will look at a practical example, explaining how we are helping a small business to make sound decisions for the future.