We’ve all seen those scenes from sci-fi movies where a scientist runs a program and then an artificial intelligence (AI) model magically appears to provide some mind-blowing results. It would be great if we could simply ask our AI model to provide us with output without having to first provide it with a data set. However, this is not how AI works. In order for an AI model to provide us with the desired product, it must first be trained on a data set. Data is a critical component of AI and deep learning that provides the foundation needed to create robust AI and predictive models. Sometimes, real data can be insufficient or inaccurate. To make effective use of data, it is imperative to conduct a thorough qualitative control and quantitative assessment. In most cases, the lack of quality resources is identified as the main obstacle to successful data-based decision-making.