How to do the right thing first and create data pools by Prof. Dr. Chris Schlueter Langdon
Doing the right thing first
Artificial Intelligence (AI) feeds on data. Particularly, neural networks and deep learning, such as TensorFlow, have a voracious data appetite. Yet, despite its importance, data often remains an afterthought. Typically, planning for a new data analytics project is occupied with debates about the right skill set of data scientists, the right tools, deadlines and, of course, budget. As a result, most of the time of a data analytics project (measurements range from 50% to < 80%) is consumed with data search, collection, and refinement. A key solution to saving time and money is to specify data needs upfront and create data pools accordingly.