Operating AI

CHAPTER 2Data Engineering Focused on AI

It's well known that without data you can't develop and train an AI model and that you can't run an AI model in a live production setting if your data flow is interrupted or stopped. Still, companies tend to invest much less time and money on managing all aspects of the data needed than they do on developing new algorithms and models. Why is that?

Some say it's because working with the data is not that exciting, whereas developing cool algorithms is what everyone wants to do. However, in my opinion, it's the data that is cool. The data is the foundation of everything related to analytics and AI, and without it we would have nothing. It's the data that enables us to see what we previously didn't see, understand what we didn't know, and manage or achieve capabilities previously unattainable.

Treating data as one of the most valuable business assets should be the main priority in any company. It's truly the way to stay on top of what is going on in your company, and it will help you understand what is not working and why, as well as foresee what is coming in order to give you time to prevent it from happening or be prepared to respond to any challenge as quickly and efficiently as possible.

So, keeping your data in order is vital. But where do you start? A first good step is to understand what data is available to you already and how that is being used today. And before you embark on a journey to get more data, be sure to understand what ...