Multidimensional digital platform for building integration and analysis

• US 20130046569A1
• Filed: 08/15/2012
• Published: 02/21/2013
• Est. Priority Date: 08/17/2011
• Status: Active Grant

• Current Assignee: Douglass Humphreys, Hadar Wissotzky, Mark Raymond Miller, Natan Goore, Rachel Posman, Signo Uddenberg
• Original Assignee: Douglass Humphreys, Hadar Wissotzky, Mark Raymond Miller, Natan Goore, Rachel Posman, Signo Uddenberg
• Inventors: Miller, Mark Raymond, Wissotzky, Hadar, Goore, Natan, Humphreys, Douglass, Uddenberg, Signo, Posman, Rachel
• Granted Patent: US 10,147,053 B2
• Time in Patent Office: Days
• 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 system is provided for qualifying and analyzing data for at least one business intelligence. A platform receives source data. A data management system transforms raw data and stores it. An analytic engine is included. In operation the data management system receives first, second, and third streams of source data. The first stream is client source data, the second stream is public source data and the third stream is acquired by the data management system. The data management system organizes the first, second and third streams of data into items and their attributes. The analytic engine receives the items with their attributes from the data management system and applies logic to provide multi-dimensional analysis relative to a scale for at least one business intelligence.

Claims

1. A system for qualifying and analyzing data for at least one business intelligence, comprising:

a platform that receives source data;

a data management system that transforms raw data and stores it;

an analytic engine;

wherein in operation the data management system receives first, second, and third streams of source data, the first stream of data being client source data, the second stream of data being public source data and the third stream being data acquired by the data management system;

the data management system organizing the first, second and third streams of data into items and their attributes; and

the analytic engine receiving the items with their attributes from the data management system and applying logic to provide multi-dimensional analysis relative to a scale for at least one business intelligence.

2. The system of claim 1, further comprising:

analysis and report preparation logic.

3. The system of claim 1, further comprising:

a user interface that a user uses to interact with the platform.

4. The system of claim 1, further comprising:

a peer network.

5. The system of claim 1, further comprising:

adaptive intelligence logic.

6. The system of claim 1, wherein the source data includes first, second and third streams of source data.

7. The system of claim 1, wherein client source data is data provided by a client and is specific to that client.

8. The system of claim 7, wherein the client source data is related to at least one of, facility assets;

human factors;

cultural factors;

user data;

environmental resource data;

scheduling data;

financial data; and

custom data.

9. The system of claim 1, wherein the public source data is data is accessed from public resources.

10. The system of claim 9, wherein the public source data is data related to at least one of:

facility assets;

human factors;

cultural factors;

user data;

environmental resource data;

scheduling data;

financial data; and

custom data.

11. The system of claim 1, wherein the data management system proprietary data is collected by the data management system team based on the needs of the specific project.

12. The system of claim 1, wherein the data management system transforms the raw source data into a format and logic usable by the platform.

13. The system of claim 1, wherein the data management system consists of an extract-transform-loader (ETL) and a data warehouse.

14. The system of claim 13, wherein the ETL includes a data transformer and a data validator;

the data transformer including at least one of;

assignment logic for assigning raw source data to predefined data management system database fields;

association logic for associating raw data through item/attribute relationships;

dimension logic for classifying raw data as asset-related, environment-related, or culture-related dimensions;

or time or value-related scale logic for relating items to each other based on scale; and

qualifying logic for qualifying raw data based on data-related collection methods.

15. The system of claim 14, with the data validator further comprising;

logic for determining if the raw data is valid for input into the data management system database, the validation logic including a set of rules governing valid data format and valid data value for the item or attribute type.

16. The system of claim 14, with the ETL and data validator further comprising;

logic for assigning metadata to the raw data during classification and qualification.

17. The system of claim 15, with the metadata being used for analysis, evaluation, and reporting.

18. The system of claim 13, wherein the data warehouse 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

indices.

19. The system of claim 18, wherein the indices database includes both data collected from public sources and information calculated internally.

20. The system of claim 19, wherein the data collected is selected from at least one of, building standards, occupancy standards, classroom standards, cost of construction data, thermal comfort standards, and the like.

21. The system of claim 1, wherein the analysis and report preparation system runs multi-dimensional analysis on data in the data warehouse and prepares reports relating the analysis to short-term and long-term value information related to client priorities.

22. The system of claim 17, wherein the analysis and report preparation system consists of an analytic engine, a data analysis evaluator, and a report builder.

23. The system of claim 22, wherein the analytic engine comprises:

an analytic operator that interprets user queries;

a data aggregator that aggregates items and attributes at different scales;

a data analyzer that executes multi-dimensional calculations, comparisons, correlations, and other operations on selected data sets.

24. The system of claim 23, wherein the analytic operator consists of:

query Interpretation logic to interpret user queries related to a specific client assignment; and

data retriever logic to determine which data sets are required from the data warehouse to execute the requested analysis.

25. The system of claim 23, wherein the data aggregator consists of logic to aggregate attributes from a more detailed scale into an attribute(s) for an item in a less detailed scale.

26. The system of claim 23, wherein the data analyzer runs logic selected from at least one of;

comparison logic to compare data sets within a single dimension or across dimensions, over time, and related to value;

math logic to calculate averages, minimums, maximums, ranges, and other mathematical functions on a data set within a single dimension or across dimensions;

correlation logic to correlate attributes to outcomes expressed as value, data set calculations, or other within a single dimension or across dimensions.

27. The system of claim 26, wherein the operation of one logic may involve an input that is the result of another logic.

28. The method of claim 26, wherein use of a logic includes a single dimension or multiple dimensions of data leading to different orders of data management system analysis, the orders including:

first order data management system analysis with data from a single dimension of asset, environment, or culture;

second order data management system analysis with data from at least two dimensions of asset, environment, and/or culture; and

third order data management system analysis with data from three dimensions of asset, selected from at least one of, asset, environment, and/or culture.

29. The system of claim 22, wherein the data analysis evaluator consists of a logic for calculating a quality score for the information generated by the analytic engine, with the score being based on qualifier metadata.

30. The system of claim 22, wherein the report builder communicates with the analytic engine and data analysis evaluator to generate reports related to specific client assignments.

31. The system of claim 22, wherein the reports generated by the report builder are packaged for presentation to the user in terms of capital and operational allocations determined by client priorities.

32. The system of claim 31, wherein capital and operational allocations relate to value data coming from at least one of client databases, indices, or other external value-related sources.

33. The system of claim 1, wherein the user interface is configured to allow users to perform at least one of:

define a project, set organization priorities selected from at least one of, input data;

build queries to define specific assignments;

view data, and view reports.

34. The system of claim 5, wherein the adaptive intelligence logic performs at least one of:

recognizes patterns in user interaction;

measures predicted verses actual outcomes;

calibrates data management system proprietary data; and

adjusts the rules used by the data validator in the data management system.

35. The system of claim 34, wherein calibration refers to refining the accuracy of the proprietary data.

36. The system of claim 1, wherein the peer and public network advisor provides data and information context to client reports by providing at least one of:

comparison of a first client specific report to one or more second client specific reports;

comparison of client information to public and/or industry trends related to that information;

comparison of client information to information from their peer network; and

comparison of client information to information from similar projects with publicly available information.