Entity resolution software
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Definition
What is entity resolution?
Entity resolution, is a core data quality process used to identify records that refer to the same entity within or across data sources. This could be done for deduplication and cleansing purposes, or to enrich and create golden records that absorb entity fragments across your business and create a unified entity profile.
As data grows at unexpected speed, the process of entity resolution is also getting complicated. It is difficult to find uniquely identifying attributes residing across databases for the same entities. And so, complex and specialized data cleansing, matching, and merging capabilities are required in fields of crime detection, law enforcement, finance and insurance, etc.
Process
How does entity resolution work?
Ingestion
Bring data together at one place, since it is scattered across disparate sources, and resolve any conflicting changes in database schemas to allow further processing.
Data standardization
Fix data standardization issues highlighted in the previous step, including filling in empty data, replacing inaccurate or invalid information, standardizing values against defined patterns and formats, etc.
Canonicalization
Merge information from duplicate records with the help of canonical rules, so that maximum information is combined into one golden record which represents the completeness of that entity.
Data discovery
Discover and highlight any statistical anomalies that may be present in the form of missing, incomplete or invalid data values.
Entity record linking
Match records within and across databases and identify potential records that relate to the same entity. Datasets usually lack standardized uniquely identifying attributes, and so a combination of intelligent fuzzy matching algorithms may be needed to increase accuracy.
Canonicalization
Merge information from duplicate records with the help of canonical rules, so that maximum information is combined into one golden record which represents the completeness of that entity.
Solution
Let Data Ladder handle your entity resolution process
See DataMatch Enterprise at work
DataMatch Enterprise is a highly visual and intuitive data scrubbing software that has the suite of features to inspect, reconcile, and remove data errors at scale in an intuitive and affordable manner.
DataMatch leverages a plethora of industry-standard and proprietary algorithms to detect phonetic, fuzzy, mis-keyed, and abbreviated variations. The suite allows you to build scalable configurations for data standardization, deduplication, record linkage, enhancement, and enrichment across datasets from multiple and disparate sources, such as Excel, text files, SQL and Hadoop-based repositories, and APIs.
Business benefits
How can entity resolution benefit you?
Customer identity resolution
Reconcile conflicting identities by creating unified customer profiles to confidently track customers across omni-channel interactions.
Enhanced Patient matching
Ensure efficient and timely healthcare diagnosis and treatment by matching patient IDs correctly with EHR records.
Fraud prevention
Detect fraudulent activities such as overdue payments or multiple claims within or across several datasets with unique identifiers.
Lower customer acquisition costs
Remove duplicates from contact lists, CRMs, and databases to avoid marketing expenditure on erroneous and redundant leads.
Regulatory compliance
Accurately match datasets against watchlists to comply with federal including OFAC, KYC, AML, and much more.
Lower time-to-insight
Improve time-to-insight from weeks to hours by saving hundreds of man-hours and complete projects weeks ahead of deadlines.
Let’s compare
How accurate is our solution?
In-house implementations have a 10% chance of losing in-house personnel, so over 5 years, half of the in-house implementations lose the core member who ran and understood the matching program.
Detailed tests were completed on 15 different product comparisons with university, government, and private companies (80K to 8M records), and these results were found: (Note: this includes the effect of false positives)
| Features of the solution | Data Ladder | IBM Quality Stage | SAS Dataflux | In-House Solutions | Comments |
|---|---|---|---|---|---|
| Match Accuracy (Between 40K to 8M record samples) | 96% | 91% | 84% | 65-85% | Multi-threaded, in-memory, no-SQL processing to optimize for speed and accuracy. Speed is important, because the more match iterations you can run, the more accurate your results will be. |
| Software Speed | Very Fast | Fast | Fast | Slow | A metric for ease of use. Here speed indicates time to first result, not necessary full cleansing. |
| Time to First Result | 15 Minutes | 2 Months+ | 2 Months+ | 3 Months+ | |
| Purchasing/Licensing Costing | 80 to 95% Below Competition | $370K+ | $220K+ | $250K+ | Includes base license costs. |
Frequently asked questions
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