Big Data MBA

Chapter 8Thinking Like a Data Scientist

One of the most frequent questions I get is: “How do I become a data scientist?” Wow, tough question. There are many outstanding books and university courses that outline the different skills, capabilities, and technologies that a data scientist is going to need to learn and eventually master. I've read several of these books and am impressed with the depth of the content.

Most of these books spend the vast majority of their time covering topics such statistics, data mining, text mining, and data visualization techniques. Yes, these are very important data science skills, but they are not nearly sufficient to make our data science teams effective. And it is not practical, or even beneficial, to try to turn your entire workforce into data scientists. Nevertheless, it is realistic to teach the business stakeholders to “think like a data scientist” in order for the business stakeholders to understand the types of business opportunities that can be driven by applying predictive and prescriptive analytics to new sources of customer, product, and operational data and to help the data science team to uncover those variables and metrics that are better predictors of performance.

The potential of thinking like a data scientist first hit me when I was the Vice President of Advertiser Analytics at a large Internet portal company. I was chartered with building the analytics to help our advertisers and agencies improve the performance of their marketing ...