Providing a multi-tenant knowledge network
Business intelligence, decision support and knowledge management network systems and methods provide efficient, robust, and business-friendly services for the rapid analysis of massive amounts of business, electronic, and other disparate data into actionable intelligence. An advantageous element of the multi-party knowledge network allows the aggregation of common data formats in order to analyze a combined dataset consisting of information from multiple parties, thereby providing additional business intelligence than with a single set of data alone.
1. A computer-implemented method for generating multi-tenant analytics data, the method comprising:
obtaining, by a processing device, raw data from a plurality of different data sources, wherein the plurality of different data sources comprise a plurality of different business entities;
analyzing, by the processing device, the raw data to identify one or more data structures of the raw data;
generating a plurality of Universal Data Model (UDM) constructs, each UDM construct based at least in part on the identified one or more data structures of the raw data, wherein each UDM construct is different and corresponds to a particular identified one or more data structures of the raw data;
integrating, by the processing device, the raw data from the plurality of different data sources by extracting, transforming, and loading the raw data such that the raw data conforms to the UDM construct for the identified one or more data structures of the raw data, wherein the integrating generates UDM transformed data; and
generating, by the processing device, the multi-tenant analytics data, wherein the generated multi-tenant analytics data is based on the UDM transformed data, and wherein the UDM transformed data is associated with at least two different data sources of the plurality of different data sources.
2. The computer-implemented method of claim 1 , wherein the plurality of different business entities comprise a plurality of different units within a single business entity.
3. A system comprising:
a hardware processor;
Universal Data Model (UDM) modeling logic, implemented by the hardware processor operating on executable instructions, configured to:
obtain raw data from a plurality of different data sources, wherein the plurality of different data sources comprise a plurality of different business entities,
analyze the raw data to identify one or more data structures of the raw data, and
generate a plurality of UDM constructs, each UDM construct based at least in part on the identified one or more data structures of the raw data, wherein each UDM construct is different and corresponds to a particular identified one or more data structures of the raw data;
an integration unit, implemented by the hardware processor operating on executable instructions, operatively connected to the UDM modeling logic, the integration unit configured to integrate the raw data from the plurality of different data sources by extracting, transforming, and loading the raw data such that the raw data conforms to the UDM construct for the identified one or more data structures of the raw data, wherein the integrating generates UDM transformed data; and
an analytical application unit, implemented by the hardware processor operating on executable instructions, operatively connected to the integration unit, the analytical application unit configured to generate multi-tenant analytics data based on the UDM transformed data, wherein the UDM transformed data is associated with at least two different data sources of the plurality of different data sources.
4. The system of claim 3 , further comprising a back-end analytics unit.