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

• US 8,571,909 B2
• Filed: 08/15/2012
• Issued: 10/29/2013
• Est. Priority Date: 08/17/2011
• Status: Active Grant

• Current Assignee: Roundhouse One LLC
• Original Assignee: Roundhouse One LLC
• Inventors: Miller, Mark Raymond, Wissotzky, Hadar, Goore, Natan, Humphreys, Douglass, Uddenberg, Signo, Posman, Rachel
• Primary Examiner(s): Jarrett, Scott L
• Application Number:
  US13/586,529
• Publication Number:
  US 20130046570A1
• Time in Patent Office: 440 Days
• Field of Search: 705/7.11, 703/1
• US Class Current: 705/7.11
• CPC Class Codes: G05B 19/182 characterised by the machine tool function, e.g. thread cutting, cam making, tool direction control G05B19/21 - G05B19/40 take precedence
• CPC Class Codes: G05B 19/4065 Monitoring tool breakage, life or condition
• CPC Class Codes: G06F 16/20 of structured data, e.g. relational data
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/063114 Status monitoring or status determination for a person or group
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A method is provided for qualifying and analyzing business intelligence. At a first part of a data management system receives first, second and third streams of data. The first stream is client provided source data, the second is public source data and the third is data management system internal data previously collected and managed source data in the data management system. The three streams of data are organized into items and their attributes at the data management system. The source data is transformed at a data warehouse where it becomes normalized. Logic is applied to provide multi-dimensional analysis of transformed source data relative to a scale for at least one business intelligence. The data warehouse includes updated data from the multi-dimensional analysis. A user interface communicates with the data management system to create statistical information that illustrates impact over time and value.

Claims

1. 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; and

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.

2. The method of claim 1, further comprising:

providing a data warehouse that includes a plurality of databases, selected from at least one of, data management system database, distinct client databases;

qualifier metadata;

peer network metadata; and

data management system client historical data; and

an Indices database.

3. The method of claim 1, wherein an indices database includes both data collected from public sources and information calculated internally by the data management system.

4. The method of claim 1, further comprising:

generating reports through a report builder that are packaged for communication to a user.

5. The method of claim 1, further comprising:

using capital and operational allocations that relate to value data coming from at least one of client databases, indices, or other external value-related sources.

6. The method of claim 1, further comprising:

setting organization priorities, wherein the organization priorities are selected from at least one of, input data;

build queries in response to specific business problems; and

analytic results.

7. The method of claim 1, wherein multi-dimensional analysis operates on items and or attributes selected from at least one of, comparing, calculating and correlating.

8. The method of claim 1, wherein scale of time scaling is a level of detail of an analysis relative to the dimension under study.

9. The method of claim 1, wherein a user interface is used that has a series of applications which relate to the analytic engine.

10. The method of claim 1, further comprising:

using a scaling function to organize and communicate the source data.

11. The method of claim 1, wherein client provided data or transformed data has organized indices that relate to at least one, proprietary data, collected data, peer data and benchmark data.

12. The method of claim 1, wherein the first, second, and third streams of data become data management system transformed data.

13. The method of claim 1, further comprising:

validating the transformed data by filtering errors and extraneous elements to create validated data management system transformed data.

14. The method of claim 13, further comprising:

applying one or more study criteria to a specific assignment.

15. The method of claim 14, wherein at least one of a study criteria is a human or cultural factor.

16. The method of claim 14, wherein at least one of an other criteria is an environmental factor.

17. The method of claim 14, wherein at least one of a criteria is an asset factor.

18. The method of claim 1, further comprising:

creating ratings relative to a quality of the data management system transformed data to create rated data management system transformed data.

19. The method of claim 1, further comprising:

organizing specific data management system transformed data from a data warehouse into a specific assignment.

20. The method of claim 1, further comprising:

applying a time sensitive model to the analyzed data to create at least one of, a historic, current and projected performance of an assignment.

21. The method of claim 20, wherein the value is measured by financial and other parameters related to the time sensitive model.

22. The method of claim 1, wherein the value is measured by financial and other parameters.

23. The method of claim 22, wherein the value is selected from at least one of, financial, sustainability, wellness, productivity, brand awareness, schedule, efficiency and utilization, that may be related to the study criteria.

24. The method of claim 23, further comprising:

prioritizing at least two of the values by ranking and rating.

25. The method of claim 22, wherein the value allows the client to perform informed business intelligence related to one or more dimensions against a client'"'"'s priorities or study criteria.

26. The method of claim 1, wherein the client provided source data includes at least one of, facility asset data, environmental resource data, financial data, cultural data and schedule data.

27. The method of claim 1, wherein the public source data includes at least one of, facility asset data, environmental resource data, financial data, cultural data and schedule data.

28. The method of claim 1, wherein data previously collected and managed in the data management system includes at least one of, data collected from other clients, propriety data of a warehouse, previously collected client data, data collected from third party clients, and peer data.

29. The method of claim 1, wherein time is a level of description of an analysis relative to at least one of, historic conditions, current status and projected modeling.