Our world is complex and no single approach exists that solves all problems. Likewise, in the data world one cannot solve all problems with one piece of technology.
Nowadays, any big technology company uses (in one form or another) a MapReduce paradigm to sift through terabytes (or even petabytes) of data collected daily. On the other hand, it is much easier to store, retrieve, extend, and update information about products in a document-type database (such as MongoDB) than it is in a relational database. Yet, persisting transaction records in a relational database aids later data summarizing and reporting.
Even these simple examples show that solving a vast array of business problems requires adapting to different technologies. This means that you, as a database manager, data scientist, or data engineer, would have to learn all of these separately if you were to solve your problems with the tools that are designed to solve them easily. This, however...