A relational database management system (RDBMS) is great at answering random questions. In fact, that is why it was invented. A normalized data model represents the lowest common denominator for data. It is agnostic to all access patterns and optimized for none.
The mission of the IBM System R team, creators of arguably the first RDBMS, was to enable users to query their data without having to write complex code requiring detailed knowledge of how their data is physically stored. Edgar Codd, inventor of the RDBMS, made this claim in the opening line of his famous document, “A Relational Model of Data for Large Shared Data Banks”:
“Future users of large data banks must be protected from having to know how the data is organized in the machine.”
The need to support online analytical processing (OLAP) workloads drove this reasoning. Users sometimes need to ask new questions or run complex reports on their data. Before the RDBMS existed, this required software engineering skills and a significant time investment to write the code required to query data stored in a legacy hierarchical management system (HMS). RDBMS increased the velocity of information availability, promising accelerated growth and reduced time to market for new solutions.