Data Science Project Stages (Part - I)

1. Understand the problem

Before we jump into the project, we must speak with the person who presented the business problem at first place. It's important to get cleared couple of things as i) what the problem is all about. ii) why it must be resolved now. iii) Who are the key stakeholders. iv) What are the expectations from this project. Without this step the outcome may be unacceptable.

2. Develop Industry knowledge:

If you have previous working knowledge of the sector within which you are asked to work, you are off to a great start. You can apply your existing experience to the problem. May be already know the potential solution (s).

If you do not have industry knowledge, all is not lost. You got the opportunity to learn something new. Spend some time researching it in more details. i) What are the common pitfalls in the industry. ii) Have your company competitors run into same problems. if so try to know if possible through resources. iii) Try multiple resources to gain the knowledge like internet, books, interviews, videos etc. But ultimately always remember as a data scientist you are not working in a vacuum. Having solid knowledge of the environment within which you are operating, as well as it's individual characteristics and limitations will help you to devise an approach.

3. Act like Consultant:

Consultant tend to be people who have worked in the industry for lone time and they will have a lot of knowledge about the sector. These people are often involve in improving the large scale business strategies and organizational aspects. Prepare list of the key stakeholders for the project and make special note of who are the final decision makers.