Adaptive data cleaning

• US 20060238919A1
• Filed: 05/27/2005
• Published: 10/26/2006
• Est. Priority Date: 04/20/2005
• Status: Abandoned Application

• Current Assignee: The Boeing Co.
• Original Assignee: The Boeing Co.
• Inventors: Bradley, Randolph L.
• Application Number:
  US11/139,407
• Publication Number:
  US 20060238919A1
• Time in Patent Office: Days
• US Class Current: 360/128
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination

Abstract

A data cleaning process includes the steps of: validating data loaded from at least two source systems; appending the validated data to a normalized data cleaning repository; selecting the priority of the source systems; creating a clean database; loading the consistent, normalized, and cleansed data from the clean database into a format required by data systems and software tools using the data; creating reports; and updating the clean database by a user without updating the source systems. The data cleaning process standardizes the process of collecting and analyzing data from disparate sources for optimization models enabling consistent analysis. The data cleaning process further provides complete auditablility to the inputs and outputs of data systems and software tools that use a dynamic data set. The data cleaning process is suitable for, but not limited to, applications in aircraft industry, both military and commercial, for example for supply chain management.

Claims

1. A data cleaning process, comprising the steps of:

validating data loaded from at least two source systems using data formatting utilities and data cleaning utilities;

appending said validated data to a normalized data cleaning repository;

selecting the priority of said source systems;

creating a clean database containing unique data identifiers for each data element from said at least two source systems;

creating and maintaining a cross-reference between said unique data identifiers;

loading consistent, normalized, and cleansed data from said clean database into a format required by data systems and software tools using said data;

creating standardized data cleaning and management reports using said consistent, normalized, and cleansed data; and

updating said consistent, normalized, and cleansed data by a user without updating said source systems.

2. The data cleaning process of claim 1, further including the steps of:

loading data from said at least two source systems to a common format for data cleaning using an extract, transformation, and load tool;

creating a master table of data elements and sources as a single source of item data containing the best value of each of said data elements;

attaching a note to each of said data elements providing additional understanding of said data element and maintaining notes in said master table of data elements and sources;

maintaining traceability to said source system of each of said data elements;

creating a unique reference number for each of said data elements enabling said data systems and software tools to receive a unique item identification number; and

maintaining an indentured master data item list containing said unique item identification number.

3. The data cleaning process of claim 1, wherein said data validating step further includes the steps of:

normalizing said data loaded from at least two source systems to a common format;

adjusting unique data identifiers to a common format;

flagging invalid, unrecognized, and missing item identifiers for review; and

cleaning said data loaded from at least two source systems.

4. The data cleaning process of claim 1, further comprising the steps of:

providing traceability to all versions of data from each of said source systems; and

providing an audit trail to previous values of data to be pulled as of a historical point of time.

5. The data cleaning process of claim 1, further comprising the steps of:

determining the number of unique data elements;

determining the number of said source systems for each of said unique data elements;

selecting said source system for each of said unique data elements according to a user specified priority;

updating said priority for a particular data pull by the user; and

maintaining a historical record of all prioritizations.

6. The data cleaning process of claim 1, further comprising the steps of:

creating line count reports;

tallying the number of said unique item identifiers in said master table of data elements and sources; and

cross tabulating said unique item identifiers against different data elements.

7. The data cleaning process of claim 1, further comprising the steps of:

creating high driver reports;

prioritizing items for review; and

identifying obvious errors rapidly.

8. The data cleaning process of claim 1, further comprising the step of:

enabling closed loop data cleaning by providing a data cleaning user interface that enables said user to update said master table of data elements and sources.

9. A data cleaning process for a supply chain, comprising the steps of:

loading data from multiple source systems to a master table of data elements and sources;

selecting precedence of said source systems;

cleaning logistics data contained in said master table of data elements and sources based on high driver and error reports;

approving consistent, normalized, and cleansed data of said master table of data elements and sources and providing said cleansed data to data systems and software tools using said data;

initiating inventory optimization of stock level and reorder points using a strategic inventory optimization model using said cleansed data;

providing a spares analysis including stock level and reorder point recommendations;

archiving supporting data for customer audit trail;

creating reports; and

purchasing spares to cover shortfalls according to said reports.

10. The data cleaning process for a supply chain of claim 9, further including the steps of:

extracting said data from said source systems;

executing conversion of said data to a common format for data cleaning; and

reviewing said high driver and error reports.

11. The data cleaning process for a supply chain of claim 9, further including the steps of:

extracting and converting data from said master table of data elements and sources for said strategic inventory optimization model, and

exporting said data from said strategic inventory optimization model to said reports for said spares analysis.

12. The data cleaning process for a supply chain of claim 9, further including the steps of:

approving inventory optimization;

reviewing said spares analysis using reports and web views; and

exporting said stock level and reorder point recommendations, strategic model inputs, source system information, and comments from said strategic inventory optimization model to a data repository.

13. The data cleaning process for a supply chain of claim 9, further including the steps of:

exporting said stock level and said reorder points to an inventory management system; and

updating said inventory management system for said stock level and said reorder points to an inventory management data warehouse for asset management.

14. A data cleaning system, comprising:

data formatting utilities, wherein said data formatting utilities are used to validate data downloaded from at least two source systems;

data cleaning utilities, wherein said data cleaning utilities are used to clean said data;

a normalized data cleaning repository, wherein said normalized data cleaning repository receives said formatted and cleansed data;

source prioritization utilities, wherein said source prioritization utilities are used to select the priority of said at least two source systems;

a clean database, wherein said clean database combines said cleansed and prioritized data, and wherein said clean database is a single source of item data containing the best value and unique data identifiers for each data element;

cross-reference utilities, wherein said cross-reference utilities are used to create and maintain a cross-reference between said unique data identifiers; and

a data cleaning user interface, wherein said data cleaning user interface enables a user to update said clean data base.

15. The data cleaning system of claim 14, further comprising an extract, transform, and load tool, wherein said extract, transform, and load tool extracts said data from said at least two source systems, transforms said data to a common format for data cleaning, and loads said data into said data cleaning system.

16. The data cleaning system of claim 15, wherein said extract, transform, and load tool is used to load said data from said clean database into a format required for data systems and software tools using said data.

17. The data cleaning system of claim 14, wherein said clean database is a master table of data elements and sources.

18. The data cleaning system of claim 17, further comprising standardized data cleaning and management reports, wherein said reports may be created from said data contained in said master table of data elements and sources.

19. The data cleaning system of claim 14, wherein said data cleaning utilities are used to ensure validity of data loaded from said source systems into said data cleaning format.

20. The data cleaning system of claim 14, wherein said source prioritization utilities maintain a historical record of previous prioritizations.

21. The data cleaning system of claim 14, wherein said master table of data elements and sources maintains traceability to the source of each data element.

22. The data cleaning system of claim 14, wherein said data cleaning system receives data from said at least two source systems, wherein said data cleaning system provides consistent, normalized, and cleansed data to said data systems and software tools, and wherein a user may update said data cleaning system without updating said source systems.

23. The data cleaning system of claim 22, wherein said software tool is supply chain software.

24. The data cleaning system of claim 22, wherein said data system is an inventory management system.