The decision between a data lake vs warehouse often comes down to flexibility and the type of information being stored. A lake can store both structured and semi-structured and unstructured information, and is ideal for machine learning and exploration and large-scale storage. A warehouse tends to be more specific with information, for reporting and business intelligence. These are not the only factors on which companies should rely. They should also take into account security, governance, performance and operating costs before making a decision. Teams can use the guidance of experts such as a data consulting agency, Datalance, in order to make the decision based on the real workloads.