Our Data Science approach

Our Data Science approach

May 12, 2021

Data science is a powerful tool. We think about data science differently than most organizations. Many data science teams do four things that we fundamentally disagree with:

  1. Present a solution, not a story
  2. Create a one-size fits all solution
  3. Think Machine Learning is Data Science
  4. Pretend Data science is engineering

We are story tellers

Data is cool and charts can be pretty. However, you're not considering working with us to have to make all the inferences yourself. We consider ourselves story tellers and your data contains everything we need to construct a compelling narrative.

One-size fits one

There are certainly some ways to productize a solution involving data science, but they are few and far between. Your data is valuable and needs to be handled with care and love. Plugging it into a solution that worked for someone else's data might be a good place to start, but it's superficial.

We treat each one of our customers data with the respect it deserves and are able to get the most out of it.

Machine learning for some, Data Science for everyone

Machine learning is hot right now. We work with lots of people who come into the conversation asking for a machine learning solution. We love our machine learning algorithms and we're pretty darn good at building them, but the reality is that they're not for every solution.

That also doesn't mean you don't need data science. Our team has a lot of tricks up their sleeves and we can give you an incredible solution. We'll walk through everything with you and design a solution for you that gets you a promotion.

Data Science is not Engineering

As more software companies are finding ways to fold in data science into their products, we've seen this more and more. There is a fundamental difference between data science and engineering. Engineering starts with a solution and the project is designed backwards in linear steps to accomplish it. Data science is much more like a laboratory experiment. To do it properly, you need to start with a question, develop a hypothesis, test, and iterate.

This approach is fundamental in our success. Utilizing our resources properly and keeping them focused on achieving a specific business objective means that we're faster and and maximize your investment.

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