WinPure’s AI Data Match is a purpose-built solution for entity resolution & deduplication. It applies common-sense principles to identify and link records across various data sources and leverages a global database name system to accurately match entities, even with inconsistencies or variations in data. See how you can identify duplicates, find hidden identities, and resolve entities in just three steps.
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WinPure incorporates a robust, culturally-aware name library, pretrained on an extensive dataset of 800 million global names. This sophisticated technology enables our AI to:
WinPure’s purpose-built AI engine uses advanced comparators to identify possible duplicates based on the knowledge it holds about data structures. Get:
Want granular control? WinPure’s fuzzy and exact match algorithms are designed for users who want a controlled match process. Set thresholds, assign match scores and take full control of your match parameters. Get:
The AI technology comes equipped with a global address parsing ability that allows users to compare, match, and parse global addresses right down to individaul components such as street number, street name, city, state, province, postal code, and country. The tool:
We’ve helped businesses & government organizations across the US, UK, AUS, CAD, and other countries improve their data quality.
SME businesses served
data matching accuracy
Customer retention rate
Customer data in marketing is one of the most problematic in terms of consistency and completeness. Because the data is collected via multiple sources, it is impossible to have clean data. WinPure can be used by marketing teams and agencies to treat, transform, and consolidate customer data, with the end goal of achieving holistic customer records.
The healthcare sector is burdened by the sensitivity and criticality of patient data. Mistakes in identity data, duplicate records, or even human errors can cause cases of misdiagnosis, flawed reports, & difficulties for the patient and their families. WinPure has worked with companies like GE Healthcare & Centura Health to clean and deduplicate data while maintaining accuracy, data sensitivity and integrity.
WinPure specializes in enabling local and global government bodies with identity resolution, cross-platform data match, and consolidation, as well as creating clean and accurate data. We have worked with delegated civil bodies across the US and UK, helping them with optimizing the quality of public data in a secure, on-premises environment. See how we helped local governments with data quality management.
Sports teams are now relying on quality data to get granular insights into athletes’ and coaches’ performance. Additionally, it also allows them to create innovative fan engagement strategies fueling deeper analysis and discussions. WinPure has worked with sports associations like the English Football League, West Ham United, and more on data cleaning and deduplication goals.
Media companies wrestle with vast amounts of data quality issues. WinPure offers a data management solution that tackles duplicates, corrects errors, and ensures the accuracy of audience lists, content metadata, and partner information. It streamlines data from various sources, creating a unified view for better decision-making. See how a similar organization in the media industry benefited from WinPure.
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Data inconsistencies can lead to problems like missed marketing opportunities or inaccurate reporting. Data matching helps ensure your data is unified and reliable.
Typos, different formats (e.g., John vs. Johnny), and missing information can make data matching tricky. WinPure helps overcome these challenges with advanced fuzzy matching techniques.
Data matching and record linkage are often used interchangeably, but there’s a subtle difference. Data matching focuses on finding any records that refer to the same entity, regardless of data source. Record linkage specifically refers to linking records across databases that hold similar information, typically about individuals.
WinPure offers advanced matching techniques to find matches even with discrepancies. Our tools use methods like fuzzy matching and probabilistic matching to account for variations in data. Additionally, WinPure allows you to define matching rules based on specific data points for more control.
WinPure offers deterministic matching and probabilistic matching. Deterministic matching uses exact or predefined rules to identify matches. Probabilistic matching assigns a likelihood score to potential matches, considering variations in data. WinPure helps you choose the best approach based on your specific data and matching needs.