With the evolution of the technological world, due to the large volume and diversity of data generated by various types of information systems, the traditional analysis tools have been insufficient to understand the value that each data presents. For this reason, automatic learning is perfect for exploiting hidden opportunities, that is, it is able to discover and display patterns and identify relationships between data. These data present an important value for different types of companies. The need to be at the forefront of technology is an extremely important step, as each company can adjust to changing the market by preventing its customers from switching to competing companies. The objective of this work is to establish a set of criteria for comparing a set of automatic learning tools for the treatment of large quantities of information on Big Data platforms. Based on these criteria, the user can select the best tool that fits his purpose.