Data integration method

Abstract

A data integration method involves a unique method of collecting raw business data and processing it to produce highly useful and highly accurate information to enable business decisions. This process includes collecting global data, entity matching, applying an identification number, performing corporate linkage, and providing predictive indicators. These process steps work in series to filter and organize the raw business data and provide quality information to customers. In addition, the information is enhanced by quality assurance at each step in this process to ensure the high quality of the resulting data.

1 . A system of data integration, comprising: 
 a data collection driver for collecting business information;    an entity matching driver for matching said business information to data in a database that is associated with a business entity;    an identification number driver for assigning a unique identifier to said business entity;    a corporate linkage driver for providing linkage of said business entity to a corporate family; and    a predictive indicator driver for providing statistical and analytical information about the likelihood that said business will perform in a specific way in the future;    wherein said data collection driver, said entity matching driver, said identification number driver, said corporate linkage driver, and said predictive indicator driver produce quality information for business decisions.    
   
   
       2 . The system according to  claim 1 , wherein said data collection driver collects data from a plurality of sources, said sources including private company financial data, public company financial data, courts and legal filing office data, telephone company data, direct investigation data, government registries, diversity data, payment data, news, media and the Internet.  
   
   
       3 . The system according to  claim 1 , wherein said data collection driver involves updating the data daily to ensure fresh, accurate data.  
   
   
       4 . The system according to  claim 1 , wherein said data collection driver includes collecting the data from strategic partners, in addition to collecting raw data.  
   
   
       5 . The system according to  claim 1 , wherein said data collection driver encompasses global information to ensure data is consistently available across the globe.  
   
   
       6 . The system according to  claim 1 , wherein said data collection driver involves rigorous quality assurance practices to ensure the data coming in from various sources is accurate, timely, complete and consistent.  
   
   
       7 . The system according to  claim 1 , wherein said entity matching driver matches to a proprietary database containing multiple names and addresses per record.  
   
   
       8 . The system according to  claim 1 , wherein said entity matching driver identifies and removes duplicates.  
   
   
       9 . The system according to  claim 1 , wherein said entity matching driver is able to identify matches that are not identical.  
   
   
       10 . The system according to  claim 1 , wherein said entity matching driver is able to select a match by a confidence measure.  
   
   
       11 . The system according to  claim 1 , wherein said entity matching driver uses a process of cleaning, parsing and standardizing, performing candidate retrieval, and evaluation and decision making as each match is made.  
   
   
       12 . The system according to  claim 1 , wherein said entity matching driver is quality assured by constantly refining and returning match parameters based on customer feedback, manual reviews, match learnings and advances in match technologies.  
   
   
       13 . The system according to  claim 1 , wherein said identification number driver assigns said unique identifier to a single, unique business location and never recycles said unique identifier.  
   
   
       14 . The system according to  claim 1 , wherein said identification number driver uses said unique identifier to track said business through mergers, acquisitions, control changes and the entire business life cycle, including business discontinuance.  
   
   
       15 . The system according to  claim 1 , wherein said identification number driver is used to aggregate data and identify duplicates in said database.  
   
   
       16 . The system according to  claim 1 , wherein said identification number driver is a nonindicative number.  
   
   
       17 . The system according to  claim 1 , wherein said identification number driver can be used to identify duplication in customer files as well as in said database.  
   
   
       18 . The system according to  claim 1 , wherein said identification number driver plays a key role in each of the five drivers involved in this data integration process as it is an identification key for a business record as it travels through the entire process.  
   
   
       19 . The system according to  claim 1 , wherein said identification number driver undergoes rigorous quality assurance procedures to protect against duplication and maintain the integrity of the numbering system.  
   
   
       20 . The system according to  claim 1 , wherein said corporate linkage driver provides cross-border linkage.  
   
   
       21 . The system according to  claim 1 , wherein said corporate linkage driver provides public company linkage.  
   
   
       22 . The system according to  claim 1 , wherein said corporate linkage driver provides private company linkage.  
   
   
       23 . The system according to  claim 1 , wherein said corporate linkage driver defines linkage by ownership.  
   
   
       24 . The system according to  claim 1 , wherein said corporate linkage driver can also be referenced to provide details of relationships outside of corporate ownership, including affiliations, associations, co-ops, franchises, agents, dealers and chapters.  
   
   
       25 . The system according to  claim 1 , wherein said corporate linkage driver uses quality assurance procedure to improve the accuracy, completeness, timeliness and consistency of corporate linkage data.  
   
   
       26 . The system according to  claim 1 , wherein said predictive indicator driver uses payment information.  
   
   
       27 . The system according to  claim 1 , wherein said predictive indicator driver uses public records.  
   
   
       28 . The system according to  claim 1 , wherein said predictive indicator driver uses public and private company financial information.  
   
   
       29 . The system according to  claim 1 , wherein said predictive indicator driver uses linkage data to assign risk to a responsible entity.  
   
   
       30 . The system according to  claim 1 , wherein said predictive indicator driver can be selected from the group consisting of: descriptive ratings, predictive scores, and demand estimators.  
   
   
       31 . The system according to  claim 1 , wherein said predictive indicator driver are enabled by analytic capability and data capability.  
   
   
       32 . The system according to  claim 1 , wherein said predictive indicator driver are continually monitored and adjusted to improve the overall quality and accuracy.  
   
   
       33 . A method of data integration, comprising: 
 collecting business information;    matching said business information to data in a database that is associated with a business entity;    assigning a unique identifier to said business entity;    providing linkage of said business entity to a corporate family;    providing statistical and analytical information as predictive indicators about the likelihood that said business will perform in a specific way in the future; and    producing quality business and financial information for business decisions.