How IBM does data science consulting? In 2020 IBM does data science consulting by following their vetted best-practice framework.
We will focus on a fascinating topic – the step-by-step process IBM’s data science team applies when working on a consulting project. We believe this overview can be highly beneficial for both experienced professionals and data science beginners.
We will explore a best-practice framework applied by one of the pioneer and leading companies in the field. This way, you’ll get an insider’s look at how a consulting project that involves data analysis and data science unfolds.
In addition, we will examine the results achieved in IBM’s data science consulting projects with major clients from different industries. Why is that important? Well, each of these initiatives serves as an invaluable lesson to the rest of the companies in the respective industry.
If, for example, Carrefour managed to leverage AI to improve its supply chain processes, the rest of the global hypermarket chains would basically be obliged to follow, if they want to keep up.
Let’s get right in and outline the five stages of a data science consulting project.
- Stage one – engage the firm’s CTO.
- Stage two – meet with the company’s SMEs and brainstorm.
- Three – Data collection and modeling through coding sprints;
- Four – Visualization and communication of findings;
- And finally – Follow-up projects.