CRM Data Lake Segment Queries for Accurate Account Matching
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Solution Overview
Problem
Integrating data from disparate data sources, such as CRM systems and data cloud platforms, is challenging due to asynchronous updates, technical constraints on data access and presentation, and limitations in user interface capabilities, leading to incorrect data display and inefficient resource utilization.
Innovation Solution
A series of queries are performed on disparate data stores, followed by merging and sorting the results in post-processing to generate data for display, using account identifiers to link CRM and cloud data, and employing metadata to determine relevant tables, with queries divided into blocks to manage pagination and sort order.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from disparate data sources are integrated directly, then comprehensive data coverage is achieved, but data accuracy and consistency deteriorate due to asynchronous updates and technical constraints
Solution Approach 1:
The patent segments the integration process into distinct phases: data collection from multiple sources, asynchronous update handling, validation against business rules, and staged merging. This segmentation allows each phase to be optimized independently, ensuring data accuracy while maintaining comprehensive coverage across CRM and marketing automation platforms.
Solution Approach 2:
The patent introduces an intermediary validation layer that mediates between disparate data sources and the target system. This intermediary applies business rules, data quality checks, and conflict resolution logic to ensure that integrated data maintains accuracy and consistency, preventing direct integration of potentially conflicting data streams.
2Reliability
If complex data integration processes are implemented, then data merging accuracy is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent dynamically adjusts integration parameters such as batch sizes, processing priorities, and validation thresholds based on system load, data volume, and criticality requirements. This allows the system to maintain high merging accuracy while adapting resource consumption to current conditions, preventing excessive complexity from manifesting as fixed overhead.
Solution Approach 2:
The patent implements dynamic processing where the integration approach adapts based on data characteristics, source reliability, and system state. Different merging strategies are applied selectively based on data type, update frequency, and business criticality, reducing overall system complexity by avoiding uniform complex processing for all data.
3Reliability
If comprehensive data validation is performed, then data quality is improved, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial validation strategies where not all data fields undergo the same level of validation. Critical fields required for core functionality receive exhaustive validation, while less critical fields receive streamlined validation or validation on-demand. This selective approach maintains data quality for essential elements while reducing overall processing time and resource consumption.
Data Source
AI summary
Methods and corresponding systems and apparatuses for integrating data from disparate data sources are described. A list of accounts that are accessible to a user of a customer relationship management (CRM) database may be determined. At least one segment may be determined. The at least one segment may represent a group of individuals that satisfy membership criteria associated with the at least one segment. One or more individuals that are (i) associated with a given account in the list of accounts and (ii) included in the at least one segment may be determined based at least in part on one or more queries involving data tables that reside in a data cloud platform separate from the CRM database. Information describing at least the one or more individuals may be provided for presentation in a graphical user interface (GUI).