SYSTEMS AND METHODS FOR COLLECTION AND CONSOLIDATION OF HETEROGENEOUS REMOTE BUSINESS DATA USING DYNAMIC DATA HANDLING

• US 20140040182A1
• Filed: 10/14/2013
• Published: 02/06/2014
• Est. Priority Date: 08/26/2008
• Status: Active Grant

• Current Assignee: ZeeWise, Inc.
• Original Assignee: ZeeWise, Inc.
• Inventors: Gilder, Clark S., Hix, Josh, Zalewski, Bartosz J.
• Granted Patent: US 9,411,864 B2
• Time in Patent Office: Days
• US Class Current: 707/602
• CPC Class Codes: G06F 16/254 Extract, transform and load [ETL] procedures, e.g. ETL data flows in data warehouses
• CPC Class Codes: G06F 16/256 in federated or virtual databases
• CPC Class Codes: G06F 16/273 Asynchronous replication or reconciliation
• CPC Class Codes: G06F 40/151 Transformation
• CPC Class Codes: G06Q 40/12 Accounting

Abstract

Remote data collection systems and methods retrieve data including financial, sales, marketing, operational and the like data from a plurality of databases and database types remotely over a network in an automated, platform-agnostic manner. An Extract Transform and Load (ETL) data replication method for Chart of Account (COA) standardization includes receiving a request for remote data collection to extract data from a data source; extracting data in a non-intrusive manner from the data source, wherein the data comprises non-standard COA data; and transforming one of an entire set or a subset of the extracted data based on the request based on a template or a standardized form desired for comparisons.

Claims

1. An Extract Transform and Load (ETL) data replication method for Chart of Account (COA) standardization, comprising:

receiving a request for remote data collection to extract data from a data source;

extracting data in a non-intrusive manner from the data source, wherein the data comprises non-standard COA data; and

transforming one of an entire set or a subset of the extracted data based on the request based on a template or a standardized form desired for comparisons.

2. The ETL data replication method of claim 1, further comprising:

extracting the data using a two phase process comprising a reconciliation phase and a collection phase.

3. The ETL data replication method of claim 1, further comprising:

performing the transforming as an agent side process, a server side process, or an automated client side process.

4. The ETL data replication method of claim 1, further comprising:

reforming the data as the non-standard COA data so the extracted data conforms to a new standard.

5. The ETL data replication method of claim 1, further comprising:

generating read only mapped views on the extracted data using a standard COA without modifying underlying data source.

6. The ETL data replication method of claim 1, further comprising:

presenting a graphical user interface of a Visual Cash Flow model comprising a comparison between any two members or peers using pre-categorized and normalized data with the transformed data.

7. The ETL data replication method of claim 1, further comprising:

presenting a visual graph format starting with a zero axis and applying individual data elements as either positive or negative as graphical bars from a neutral zero vertical axis in order to compare one set of business results to a national average or peer group calculated value with the transformed data.

8. The ETL data replication method of claim 1, wherein the extracting comprises:

accessing data from a plurality of accounting system files comprising heterogeneous data sets across different accounting applications; and

performing a multi-pass operation of sorting, calculating, and normalizing the data based on the plurality of accounting system files, the heterogeneous data sets, and desired peer groups for comparison to provide a consolidated data set across the different accounting applications.

9. The ETL data replication method of claim 1, wherein the extracting comprises:

accessing data from a plurality of accounting system files comprising heterogeneous data sets across different accounting applications;

performing sorting, calculating, and normalizing of the data for each of the plurality of accounting system files to provide a first set of processed data;

performing sorting, calculating, and normalizing of the data for each of the heterogeneous data sets in the first set of processed data to provide a second set of processed data;

performing sorting, calculating, and normalizing of the data for a plurality of peer groups on the second set of processed data to provide a third set of processed data; and

providing a consolidated data set from the third set of processed data.

10. The ETL data replication method of claim 8, further comprising:

defining definition files for each of the heterogeneous data sets that comprise specific collection commands defined to collect all, collect deltas between the data, recollect, find specific items, transform data locally, or transform data on the server side.

11. A remote data collection system, comprising:

a network interface;

a connection to a data source;

a processor communicatively coupled to the network interface and the connection; and

memory storing instructions for remote data collection that, when executed, cause the processor to;

receive a request for remote data collection to extract data from the data source;

extract data in a non-intrusive manner from the data source, wherein the data comprises non-standard COA data; and

transform one of an entire set or a subset of the extracted data based on the request based on a template or a standardized form desired for comparisons.

12. The remote data collection system of claim 11, wherein the instructions, when executed, further cause the processor to:

extract the data using a two phase process comprising a reconciliation phase and a collection phase.

13. The remote data collection system of claim 11, wherein the instructions, when executed, further cause the processor to:

perform the transforming as an agent side process, a server side process, or an automated client side process.

14. The remote data collection system of claim 11, wherein the instructions, when executed, further cause the processor to:

reform the data as the non-standard COA data so the extracted data conforms to a new standard.

15. The remote data collection system of claim 11, wherein the instructions, when executed, further cause the processor to:

generate read only mapped views on the extracted data using a standard COA without modifying underlying data source.

16. The remote data collection system of claim 11, wherein the instructions, when executed, further cause the processor to:

present a graphical user interface of a Visual Cash Flow model comprising a comparison between any two members or peers using pre-categorized and normalized data with the transformed data.

17. The remote data collection system of claim 11, wherein the instructions, when executed, further cause the processor to:

access data from a plurality of accounting system files comprising heterogeneous data sets across different accounting applications; and

perform a multi-pass operation of sorting, calculating, and normalizing the data based on the plurality of accounting system files, the heterogeneous data sets, and desired peer groups for comparison to provide a consolidated data set across the different accounting applications.

18. The remote data collection system of claim 11, wherein the instructions, when executed, further cause the processor to:

access data from a plurality of accounting system files comprising heterogeneous data sets across different accounting applications;

perform sorting, calculating, and normalizing of the data for each of the plurality of accounting system files to provide a first set of processed data;

perform sorting, calculating, and normalizing of the data for each of the heterogeneous data sets in the first set of processed data to provide a second set of processed data;

perform sorting, calculating, and normalizing of the data for a plurality of peer groups on the second set of processed data to provide a third set of processed data; and

perform a consolidated data set from the third set of processed data.

19. The remote data collection system of claim 17, wherein the instructions, when executed, further cause the processor to:

define definition files for each of the heterogeneous data sets that comprise specific collection commands defined to collect all, collect deltas between the data, recollect, find specific items, transform data locally, or transform data on the server side.

20. Software stored in a non-transitory computer readable medium and comprising instructions executable by a system, and in response to such execution causes the system to perform operations comprising:

receiving a request for remote data collection to extract data from a data source;

extracting data in a non-intrusive manner from the data source, wherein the data comprises non-standard COA data; and

transforming one of an entire set or a subset of the extracted data based on the request based on a template or a standardized form desired for comparisons.