Data preparation is often the most time-consuming part of any AI project. Companies usually collect data from several internal systems and then clean and structure it so algorithms can work properly. In practice, data engineers spend much more time organizing datasets than training models. When researching how companies implement a machine learning solution, I found useful explanations and real examples on https://data-science-ua.com/ that show how proper data pipelines are built.