BI tools focus on single sources of data such as Data Warehouses and offer a way of phrasing complex queries over a constrained set of data in a canned model.

BI tools seldom offer a facile way of querying large numbers of distributed spreadsheets, RDBMS and Web Services all together as if they were locally present.

This is where SDS steps in - by making Distributed Query much easier (for the first time a Business User can do this themselves rather than having to call in a programmer), SDS takes the constraints off any Model you define so that the range of questions you can ask becomes effectively limitless.

For example the US Environmental Protection Agency (EPA) publishes an annual report of 327 spreadsheets containing statistics about health, air and water quality and greenhouse gases. Analysts want to ask questions such as "is there a link between this toxic chemical and a rise in infant deaths in this part of the USA" - the range of questions that can be asked is huge.
 
Before SDS, the only way to answer these ad hoc questions was to spend time cutting and pasting data to 'line up' the answers or writing complex programs.

Like a map of all US Airport Hubs and their interconnecting flight routes, "Everything is Connected" with the SDS approach. EPA spreadsheets become represented in a similar looking 'hub and spokes' graphical model and a query is formed simply by clicking on the related concepts of interest to form a Daisy Chain.

This changes the game for people that need to explore large complex data 'spaces' - one question can be asked after another very rapidly, meaning hypotheses can be tested at a pace that matches inspiration. There is no more 'coding' - creating the Daisy Chain is enough to express your query.