Episode 6: Business understanding for Data Science

Hello! And welcome to a new edition of the Data Science Now newsletter. In this session, I talked about the importance of business understanding in the context of data science. You can hear the podcast version here:

And if you prefer you can watch the video recording here:

Remember that we will be live (almost) every Wednesday here at Linkedin, 8 PM CST :).

Here's a short recap of what I covered in the session:

I can't stress enough how important it is to have a context of a business when you do data science. Data science is a scientific field. We’re embedded in a system where we follow the scientific method but we are very close to the business (or we should be).

There’s a great shot video from Kirk Borne. He exposes that data science is a scientific field, and a very close field from business. Science applied to business. Here it is:

The data scientist is always close to the software team, that’s ok cause we code, but it should be embedded in business escenarios, not only the IT team but also the business team.  If you only check how that data performs you'll have an idea, but it’s not enough to solve a real problem.

You’re in a team of people that code, but sometimes you can get confused, you’re not there to create systems, you're not only a programmer, the goal is to be able to perform and create a way for the business to make good decisions, data driven decisions, listen to the data and the problems and transform them into a data science problem that you can solve.

Science creates different things and fields to solve different problems, the field of data science is special cause we're embedded in different fields and operation of the company, it's complicated to be a data scientist right now, but interesting of course.

Where does the position fit? A data scientist can work from the bottom, trying to understand the data. For example if you sell paper. You can try to understand how to get people to buy it with the marketing team. You can be in a different position, how can you help make a better paper, with the manufacturing team. Or in a team looking for the way to explain what you do, the psychologist (maybe). You can also manage the team. You can be in a place close to the CEO trying to get the needs of the team. Or work on the creation of articles and papers.

We have different ways of applying data science in a business. But all of the above have one thing in common, they need to understand the context of 2 things, (1) where the business is standing in the world, and the actual context of the departments or business areas they're working with.

The first, trying to understand business as a whole. You can be part of different sections, it can be confusing. When you have a new challenge, how can you understand that a business is doing? This is a compilation of processes in my experience. First, have a lot of meetings, it's not programming in an empty room, you need to talk to people, understand what they do, listen to what they say. They know what they want, maybe not how to get there.

Listen about the goal of a specific department, general goals of the company, KPIs, if you want a measurable result, you need a KPI. Read and learn about the company (this is important).

Something different but related is get the idea from those and make it a data science problem. First try to see if that can be possible, if not, prove why not.

The best two methodologies to achieve business understanding I know are the Team Data Science Process by Microsoft and the Agile Business Science Problem Framework by Business Science. Here are both of them:

Make sure to read both of them with care, and also the references they have. I talked about both of them in the session, head or see that for more also :).

The goal is to give a systematic decision making mechanism, solving problems with data, take into account what they find and create an improvement. Hopefully this session helped you see that and how to achieve it.

Always Remember:

There's no easy path, you have to practice, study, and if you want to know where you're going, you need to understand where you come from. Then you will rule the world.

Thanks for reading this, please subscribe share this with your network, it would help us a lot :)

With love by the Closter Team:

Gabriel Erives, Héizel Vázquez, Eilén Vázquez, Favio Vázquez.