How Computers Match and Join Messy Data from Different Sources
A method for merging datasets by identifying related but non-identical items using flexible matching rules rather than strict equality.
Original patent title: “Fuzzy data operations”
A method for merging datasets by identifying related but non-identical items using flexible matching rules rather than strict equality. Granted to Ab Initio Technology LLC in 2017 with 23 claims and 15 forward citations.
Key facts
Coverage
What does this patent actually cover?
This patent describes a way for computer systems to combine data from two different sources even when the information doesn't match perfectly. Instead of looking for identical values, the system uses a 'variant relation' to determine if two objects are close enough to be considered a match, such as checking if the mathematical distance between two values falls below a specific threshold. Once these matches are identified, the system evaluates the surrounding data and joins the records together to create a new, combined dataset. For example, it could link 'John Smith' in one database with 'J. Smith' in another by recognizing they are variants of the same person based on defined similarity rules.
The gap
What does this patent NOT cover?
- Does not cover simple database joins that rely on exact matches (e.g., matching primary keys that are identical).
- Does not cover human-manual data entry or manual reconciliation processes.
- Does not cover matching methods that are strictly limited to equivalence relations (where A must equal B).
- Does not cover the storage hardware itself, only the logical method of processing and joining the data.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
What made this novel
The system explicitly allows for 'non-equivalence relations,' meaning it can chain matches through intermediate data elements to find connections that aren't directly obvious, effectively building a bridge between disparate data points.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Enterprise data integration platforms
Customer data platforms (CDP) for deduplication
Automated financial record reconciliation
Master data management systems
Why it matters
The bigger picture
In large-scale data processing, data is rarely clean or perfectly formatted across different departments or companies. This patent provides a formal framework for 'fuzzy' data integration, which is essential for business intelligence, customer relationship management, and regulatory compliance where records must be consolidated despite inconsistent naming or formatting.
Filed
January 23, 2013
Granted
March 28, 2017
Market context
Who's building on this
Companies in this space
Ab Initio Technology remains a primary player in high-performance data processing. Other companies in the data integration and master data management space, such as Informatica and Talend, utilize similar logic for fuzzy matching and data quality workflows.
Market impact
This patent reinforces the shift toward automated data quality tools that reduce the need for manual data cleaning. It supports the infrastructure of modern data lakes and warehouses where disparate data sources must be unified to provide accurate business insights.
Claim 1 — Plain English
What this patent covers
This patent describes a way for computer systems to combine data from two different sources even when the information doesn't match perfectly. Instead of looking for identical values, the system uses a 'variant relation' to determine if two objects are close enough to be considered a match, such as checking if the mathematical distance between two values falls below a specific threshold. Once these matches are identified, the system evaluates the surrounding data and joins the records together to create a new, combined dataset. For example, it could link 'John Smith' in one database with 'J. Smith' in another by recognizing they are variants of the same person based on defined similarity rules.
The clever bit
The system explicitly allows for 'non-equivalence relations,' meaning it can chain matches through intermediate data elements to find connections that aren't directly obvious, effectively building a bridge between disparate data points.
What it does not cover
- Does not cover simple database joins that rely on exact matches (e.g., matching primary keys that are identical).
- Does not cover human-manual data entry or manual reconciliation processes.
- Does not cover matching methods that are strictly limited to equivalence relations (where A must equal B).
- Does not cover the storage hardware itself, only the logical method of processing and joining the data.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
PatentBrief Score
Impact Score
Moderate
Citation count
24/40
Moderately cited
Claim breadth
15/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
10/20
Granted 5–10 years ago
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$87K – $280K
Midpoint $175K · 6.6 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
The original legal language
Original claims
23 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
Anderson, A. (2017). How Computers Match and Join Messy Data from Different Sources (U.S. Patent No. 9,607,103). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/9607103/amazon-athena
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Computers Match and Join Messy Data from Different Sources cover?
A method for merging datasets by identifying related but non-identical items using flexible matching rules rather than strict equality.
Who owns patent US 9607103?
Ab Initio Technology LLC owns this patent, granted in 2017.
When does this patent expire?
This patent is expected to expire on March 28, 2037, when the invention enters the public domain.
What is patent US 9607103 cited by?
This patent has been cited by 15 later patents that build on its ideas.
What problem does this patent solve?
In large-scale data processing, data is rarely clean or perfectly formatted across different departments or companies. This patent provides a formal framework for 'fuzzy' data integration, which is essential for business intelligence, customer relationship management, and regulatory compliance where records must be consolidated despite inconsistent naming or formatting.
What does this patent NOT cover?
Does not cover simple database joins that rely on exact matches (e.g., matching primary keys that are identical).
Patent monitoring