The Path to Success in Data Science Is About Your Ability to Learn. But What to Learn?

Many great developments in data science have been made in the last decade but despite these achievements, many projects never see the light of day. As data scientists we must not only show strong technical skills but also understand the business context, effectively communicate with stakeholders, and translate their questions into actionable recommendations that drive business value. Is this reasonable or is the business looking for the new unicorns? In this blog, I will describe how the business has changed over the years, which will give a better perspective on what you may need to learn to successfully deliver data science projects. <h1>A short introduction</h1> More than a decade ago companies recognized that mining data sets can result in information that can increase revenue, optimize processes, and lower the (production) costs. This has led to a new field with new roles; the data science field with data scientists. But the needs of the business keep changing over the years. It is thus important to understand the needs of the business to know what you need to learn as a data scientist. In the next section, we will first zoom out to describe how the data science field has evolved over the last decade. This can help you to know; 1. what was important to learn, 2. what is now important to learn, and 3. what can be important to learn for future endeavors. Let’s go back in time in the next section. <a href="https://towardsdatascience.com/the-path-to-success-in-data-science-is-about-your-ability-to-learn-but-what-to-learn-92efe11e34bf">Click Here</a>