Chapter 25

Ten Mistakes to Avoid When Investing in Data Science

IN THIS CHAPTER

Bullet Underestimating the fundamental shift that data science imposes

Bullet Perceiving AI as a magic solution to any problem

Bullet Forgetting about ethical aspects

Bullet Neglecting to measure the change

Although you must focus on your data science strategy objectives in order to succeed with them, it doesn’t hurt to also learn from others' mistakes. This chapter gives you a list of ten challenges that many companies tackle in the wrong way. Each section not only describes what you should aim to avoid but also points you in the direction of the right approach to address the situation.

Don't Tolerate Top Management's Ignorance of Data Science

A fundamental misunderstanding occurs in the area of data science regarding the target group for data science training. The common view is that as long as the skill set for the data scientists themselves is improved, or for the software engineers who are training to become data scientists, you are spot-on. However, by adopting that approach, the company runs the significant risk of alienating ...

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