Entity Matching Across Disparate Data Sources
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Solution Overview
Problem
The pervasive use of email leads to time-consuming and error-prone tasks when switching between email and other data sources to match senders and update records, resulting in incomplete and stale data, which reduces productivity in digital communications.
Innovation Solution
A system and method that extracts sender data from emails to match entities across multiple data sources, such as social networks and CRM databases, retrieving and combining current data from these sources to display it adjacent to the email or in a contact listing, allowing users to select and update records seamlessly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual matching and updating between email and data sources is performed, then data accuracy can be maintained, but time consumption and error rate increase significantly
Solution Approach 1:
The system performs automatic entity matching and data synchronization without requiring manual intervention. The email client automatically extracts sender information, queries external data sources, matches entities, and updates records in the background, allowing the system to serve itself rather than requiring user operation for each matching task.
Solution Approach 2:
The system proactively retrieves and caches data from external data sources before it is needed for matching. By pre-fetching and storing data in a local cache, the system prepares matching information in advance, reducing the time required during actual email processing and eliminating the need for real-time manual lookups.
2Loss of information
If multiple data sources are manually checked and updated, then complete information can be obtained, but productivity decreases due to switching between applications
Solution Approach 1:
The system integrates multiple external data sources and the email client interface into a unified system. Data from various sources is automatically retrieved, correlated, and presented within the email client environment, merging previously separate functions into a single integrated workflow that maintains information completeness while eliminating application switching.
Solution Approach 2:
The email client is enhanced with multi-functional capabilities including automatic entity recognition, external data source integration, data matching, and record updating. This universal system performs multiple functions that previously required separate applications and manual processes, maintaining complete information while improving productivity.
3Loss of time
If automatic entity matching is implemented, then time spent on data gathering is reduced, but system complexity increases
Solution Approach 1:
The system introduces a data cache as an intermediary layer between the email client and external data sources. This cache stores pre-retrieved data locally, reducing the need for complex real-time queries and matching operations. The intermediary cache simplifies the overall system architecture by decoupling the email processing from direct external data source interactions.
4Reliability
If data is automatically retrieved from external sources, then data freshness is improved, but data synchronization complexity increases
Solution Approach 1:
The system proactively retrieves and caches data from external sources before it is needed for matching operations. By pre-fetching data and storing it in a local cache with timestamp information, the system ensures data freshness is maintained without requiring complex real-time synchronization mechanisms during email processing.
Data Source
AI summary
Techniques for performing a fuzzy match of data from multiple sources are provided. In one technique, an email address of a sender of an email message is extracted from the email message. The email address is used to retrieve, from a first data source, first entity data about one or more entities, such as users. The first entity data is used to retrieve, from a second data source, second entity data about one or more entities. First data that pertains to the sender and that originates from the first data source is combined with second data that pertains to the sender and that originates from the second data source to generate sender data. The sender data is then presented via an email client that displays the email message.