I’d hate to think there’s some merit to restating this inequality, but there probably is. Legions have been indoctrinated into thinking Microsoft’s OLAP defined OLAP, or that a product was only OLAP if it had a (usually over-simple) cube structuring.
You’d have to look past vendor-specific or academic data-structure-and-algorithm-specific treatments to see a bigger picture. Erik Thomsen worked to spread a larger idea in the 1990’s and 2000’s, if you find his OLAP Solutions books or his articles in journals from that time.
Myself, I see the cube limitations on data modelling (semantic modeling for analytics being an actual passion) as being liftable with technology not available in 1993 when “OLAP” was coined.
Personally, I was first taught about the basics of data warehousing and the needs of common OLAP workflows before ever touching a cube. Cubes were just another way of accessing and slicing the same data, but far from the only way. This has only become more apparent as more and more analytics isn't relying on the traditional RDBMS-based data warehouse structure in favour of more exotic sources.
