SYSTEMS AND METHODS FOR LINKING AND ANALYZING DATA FROM DISPARATE DATA SETS

• US 20150347624A1
• Filed: 05/29/2014
• Published: 12/03/2015
• Est. Priority Date: 05/29/2014
• Status: Abandoned Application

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Villars, Curtis
• Application Number:
  US14/290,571
• Publication Number:
  US 20150347624A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9017 using directory or table look-up use of a directory or look-up table in file systems G06F16/13
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Systems and methods for linking or matching data of disparate datasets and then performing business related data analysis. Consumer-related data of two or more disparate datasets are linked in a privacy-friendly manner, and then analyzed to provide business information and/or consumer information to clients. The linking and analysis is performed in a manner to protect personally identifiable information (PII) of the consumers. In an embodiment, a processor receives a plurality of disparate anonymized datasets originating from a plurality of different data sources, formats the de-identified data to provide a plurality of formatted anonymized datasets, and links the data entries of the de-identified individuals by matching at least date data, time data, and location data. The processor then analyzes the activity data of the linked data entries, and generates a report based on the analysis.

Claims

1. A method, comprising:

receiving, by a processor, a plurality of disparate anonymized datasets originating from a plurality of different data sources, each anonymized dataset comprising de-identified data of individuals;

formatting, by the processor, the de-identified data of each of the plurality of the disparate anonymized datasets to provide a plurality of formatted anonymized datasets, each formatted anonymized dataset containing data entries for the de-identified individuals comprising a user unique identifier (UID), date data, time data, location data, and activity data;

linking, by the processor, the data entries of the de-identified individuals of the plurality of formatted datasets by matching at least the date data, time data, and location data;

analyzing the activity data of the linked data entries; and

generating, by the processor, at least one report based on the analysis.

2. The method of claim 1, further comprising transmitting the at least one report to at least one client.

3. The method of claim 1, wherein formatting further comprises arranging, by the processor, the de-identified data of the individuals in accordance with at least one pre-determined pattern.

4. The method of claim 3, further comprising filtering the arranged de-identified data in accordance with at least one predetermined time-based criteria.

5. The method of claim 4, wherein the time-based criteria comprises at least one of a time frame, a time range, and a tolerance rule.

6. The method of claim 3, further comprising filtering the arranged de-identified data in accordance with at least one predetermined client-based criteria.

7. The method of claim 6, wherein the client-based criteria comprises at least one of a merchant identifier, a merchant type, and a merchant group.

8. The method of claim 3, further comprising:

assigning a profile identifier to each pattern of the at least one predetermined pattern; and

removing, by the processor, the UID prior to linking the data entries of the de-identified individuals of the plurality of formatted datasets.

9. The method of claim 8, further comprising storing each profile identifier in a lookup table.

10. The method of claim 9, further comprising, prior to generating at least one report:

searching, by the processor, the lookup table;

obtaining at least one user unique identifier (UID) associated with the analyzed data;

locating, by the processor, detailed de-identified data associated with the UID; and

adding, by the processor, the detailed de-identified data to the analysis.

11. The method of claim 1, wherein the at least one report describes at least one pattern of activity associated with the de-identified individuals of the plurality of anonymized datasets.

12. The method of claim 1, wherein the plurality of different data sources comprises at least two of a payment network, a merchant, a mobile network operator (MNO), a public transportation authority, and a social media organization.

13. An apparatus, comprising:

a processor;

a communication device operably connected to the processor; and

a storage device operably connected to the processor and storing instructions configured to cause the processor to;

receive a plurality of disparate anonymized datasets originating from a plurality of different data sources, each anonymized dataset comprising de-identified data of individuals;

format the de-identified data of each of the plurality of the disparate anonymized datasets to provide a plurality of formatted anonymized datasets, each formatted anonymized dataset containing data entries for the de-identified individuals comprising a user unique identifier (UID), date data, time data, location data, and activity data;

link the data entries of the de-identified individuals of the plurality of formatted datasets by matching at least the date data, time data, and location data;

analyze the activity data of the linked data entries; and

generate at least one report based on the analysis.

14. The apparatus of claim 13, wherein the storage device stores further instructions configured to cause the processor to transmit the at least one report to at least one client.

15. The apparatus of claim 13, wherein the storage device stores further instructions configured to cause the processor to, during formatting, arrange the de-identified data of the individuals in accordance with at least one pre-determined pattern in accordance with at least one of at least one predetermined time-based criteria and at least one predetermined client-based criteria.

16. The apparatus of claim 13, wherein the storage device further comprises a lookup table, and wherein the storage device stores further instructions configured to cause the processor to:

assign a profile identifier to each pattern of the at least one predetermined pattern;

remove the user unique identifier (UID) prior to linking the data entries of the de-identified individuals of the plurality of formatted datasets; and

store each profile identifier in a lookup table.

17. The apparatus of claim 16, wherein the storage device stores further instructions configured to cause the processor to, prior to generating at least one report:

search the lookup table;

obtain at least one user unique identifier (UID) associated with the analyzed data;

locate detailed de-identified data associated with the UID; and

add the detailed de-identified data to the analysis.

18. The apparatus of claim 13, wherein the plurality of different data sources comprises at least two of a payment network computer, a merchant computer, a mobile network operator (MNO) computer, a public transportation authority computer, and a social media organization computer.

19. A system, comprising:

a probabilistic engine;

an anonymized data formatting engine operably connected to the probabilistic engine; and

a reporting engine operably connected to the probabilistic engine;

wherein the probabilistic engine comprises a processor and a storage device operably connected to the processor and configured to cause the processor to;

receive, from the anonymized data formatting engine, a plurality of disparate anonymized datasets originating from a plurality of different data sources, each anonymized dataset comprising de-identified data of individuals;

format the de-identified data of each of the plurality of the disparate anonymized datasets to provide a plurality of formatted anonymized datasets, each formatted anonymized dataset containing data entries for the de-identified individuals comprising a user unique identifier (UID), date data, time data, location data, and activity data;

link the data entries of the de-identified individuals of the plurality of formatted datasets by matching at least the date data, time data, and location data;

analyze the activity data of the linked data entries; and

transmit the analysis to the reporting engine to generate at least one report.

20. The system of claim 19, further comprising a matching rules engine operably connected to the probabilistic engine, the matching rules engine configured to provide the probabilistic engine with criteria for linking the data entries of the de-identified individuals.

21. The system of claim 19, further comprising a lookup table operably connected to the anonymized data formatting engine and to the reporting engine, wherein the anonymized data formatting engine operates to:

arrange the de-identified data of the individuals in accordance with at least one pre-determined pattern;

assign a profile identifier to each pattern of the at least one predetermined pattern;

remove the UID prior to linking the data entries of the de-identified individuals of the plurality of formatted datasets; and

store each profile identifier in the lookup table.