Any organisation needs answers to questions which can't be predicted in advance. Changes in the markets, strategic imperatives, growth ambitions all need data to drive decision-making. The ability to answer these questions rapidly, without resorting to internal IT or an external service provider step changes organisational agility.
There are several different techniques for structuring (or not) the data to feed ad hoc queries, and a multitude of tools to present visualisations. We're neutral in terms of which of the tools to work with - there are different answers to that question which lie at the intersection of cost and functionality. But whether the rool is Tableau, Power BI, Qlik Sense, Saiku or one of many others, what does make a difference is how your data is structured.
For many standard data sources (sales, orders, inventory, customer retention, customer service, GL) the dimensions and the metrics are well understood. These are not new, the data is structured, it's just that the we require complete flexibility in how to slice and dice it. We use a number of different schemas to solve these common problems - connecting your source data to data cubes, and the query tool of choice to the cube.
Problem solved. Many different problems, solved.