Abstractly implemented data analysis systems and methods therefor

1. A computer-implemented method for generating business intelligence (BI) results from data obtained from a plurality of data sources, comprising:

entering a design period where a metadata construct is defined by a user, wherein the metadata construct includes at least one file or library, and wherein the user defines what data is expected in a source data set, format of the data, and how to store, organize, analyze and output the data;

exiting the design period and entering an execution period;

receiving a BI query issued to a computer resource, wherein the BI query is a natural language question asked related to an interest of a business;

matching the metadata construct to the BI query;

selecting underlying data for retrieval based upon the BI query via a machine learned model;

determining presentation format of the underlying data based upon the BI query via the machine learned model;

configuring a data analysis model by the metadata construct;

analyzing the underlying data based upon the configured data analysis model; and

outputting the analyzed data based upon the determined presentation format.

2. The method of claim 1 wherein the model is part of BI logic subcomponent which communicates with other subcomponents using APIs.

3. The method of claim 1 wherein selecting the underlying data employs a virtual cluster of computers available via the Internet.

4. The method of claim 1 wherein said data analysis employs a virtual cluster of computers available via the Internet.

5. The method of claim 1 wherein determining the presentation format employs a virtual cluster of computers available via the Internet.

6. The method of claim 1 wherein said computer resource represents a computing platform including a virtual cluster of computers available via the Internet.

7. The method of claim 1 further comprising interposing a firewall between an internal computer network, which is part of the computer resource, and the Internet.

8. The method of claim 1 wherein said computer resource represents a mixture of a virtual cluster of computers available via the Internet and internal computer network components, said internal computer network residing behind a firewall that interposes between said internal computer network and the Internet.

9. The method of claim 1 wherein the method is executed by a plurality of BI logic subcomponents which includes a mixture of legacy BI logic subcomponents and newly formed BI logic subcomponents, said plurality of BI logic components exchanging data via APIs.

10. The method of claim 5 wherein said presenting also employs said data from said metadata to manage at least one of a format and a visual aspect of said business intelligence insight.

11. A non-transitory storage medium that, when executed on a computer-implemented business intelligence (BI) system for obtaining a business intelligence insight from a plurality of data sources, causes the computer implemented system to perform the steps of:

generating a metadata construct, wherein the metadata construct includes at least one file or library, and wherein the user defines what data is expected in a source data set, format of the data, and how to store, organize, analyze and output the data;

receiving a BI query issued to a computer resource during an execution period after the design period, wherein the BI query is a natural language question asked related to an interest of a business;

matching the metadata construct to the BI query;

selecting underlying data for retrieval based upon the BI query via a machine learned model, determining presentation format of the underlying data based upon the BI query via the machine learned model;

configuring a data analysis model by the metadata construct;

analyzing the underlying data based upon the configured data analysis model; and

outputting the analyzed data based upon the determined presentation format.

12. The non transitory medium of claim 11 wherein selecting the underlying data includes a plurality of data acquisition-related subcomponents which communicate with one another using APIs.

13. The non transitory medium of claim 12 wherein said plurality of data acquisition-related subcomponents is implemented using a virtual cluster of computers available via the Internet.

14. The non transitory medium of claim 11 wherein said non transitory medium is executed using a computing platform including a virtual cluster of computers available via the Internet.

15. The non transitory medium of claim 11 wherein said metadata layer govern behaviors of a set of data presentation-related subcomponents.