Business intelligence system and method utilizing multidimensional analysis of a plurality of transformed and scaled data streams

A method for qualifying and analyzing business intelligence applied to physical assets, environment factors and cultural dimensional data and their associated attributes, comprising:

• using a processor of a data management system to receive first, second and third streams of source data, the first stream of data being client provided physical assets (A), environment factors (E) and cultural dimensional (C) source data, the second stream of data being public physical assets, environment factors and cultural dimensional source data and the third stream being internal source data from the data management systems that was previously collected physical assets, environment factors and cultural dimensional data, the physical assets include capital and operation allocations for major site improvements, fixed physical infrastructure and facilities and their associated physical building systems and immobile interior elements and the associated descriptive attributes selected from at least one of, size, location, orientation and window area, environmental resource factors refer to data that describe the natural conditions selected from at least one of, weather, microclimate, solar radiance and data relating to conditions transformed by human intervention selected from at least one of, interior conditions of room temperature, humidity, insulation values, solar transmittance, surface lighting, energy consumption and energy generation, and cultural factors refers to data associated with characteristics associated with entities selected from at least, small groups, organizational departments, societal structures, demographic classification and other designated classifications and the characteristics associated with entities of people have a potential impact upon or are impacted by the physical assets or the environmental resources;
• using a processor to organize the first, second and third streams of data according to their associated items and attributes;
• using a processor to provide multi-dimensional analysis of the data for at least one business intelligence that is defined as contributing insight into the impacts of physical assets on environmental resources or cultural factors, or the impacts of environmental resources or cultural factors on physical assets in the context of a question related to quantity, quality or efficiency of one of more business activities, where first order of analysis provides one or more A metrics, one or more C metrics and one or more E metrics, second order analysis provides one or more CA metrics where C and A intersect, one or more AE metrics where A and E interest and one or more EC metrics where E and C intersect, and third order analysis provides ACE metrics where A, C and E intersect, the processor taking a progression of complexity of analysis and findings as inputs of the first order to produce an output and is tags by scale and attribute, the first order of analysis is available as inputs for second order analysis that become outputs which are summarized in tabular and statistical methods and are further correlated as part of a central third order calculation of three different dimensions;
• using a processor to correlate data from the multi-dimensional analysis using user-inputted priorities;
• using a processor of a data analysis evaluator of the analytic engine to communicate with a strategic operator to determine relevance of the analyzed data to question business intelligence, the processor using business intelligence as improved knowledge about a business problem or a study criteria to make an informed decision;
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• applying a feedback loop to compare the analyzed data to peer or public benchmarks or trends and includes an intelligence logic that receives updated data and associates this updated data with data in the data warehouse for use by the analytic.