Cloud Treasury Analytics Platform for Disparate Data Integration
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Solution Overview
Problem
Conventional treasury systems face challenges in managing and analyzing data from disparate internal and external data sources, leading to inefficiencies and inaccuracies in data analytics and risk assessments.
Innovation Solution
A cloud-based treasury analytics platform that retrieves data from various sources, enriches and structures it using treasury-centric schemas, and executes advanced analytics and risk assessments in a secure and performant manner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored on multiple disparate internal and external data storage systems, then data can be collected from various sources, but data management and analysis become difficult and require significant manual efforts
Solution Approach 1:
The patent introduces an intermediary layer (data integration platform/cloud-based system) that sits between disparate data sources and analytical tools. This intermediary standardizes data access, handles format conversions, and manages connectivity to multiple sources (ERP systems, banking platforms, market data feeds), thereby reducing the complexity burden on end users while maintaining versatility in data source integration
2Reliability
If different internal and external systems store and manage data differently, then each system can optimize for its specific function, but retrieving, formatting, and aggregating data requires significant manual efforts
Solution Approach 1:
The system performs preliminary data standardization and enrichment actions during the data ingestion phase. Data is pre-formatted, validated, and enriched with additional context (such as entity relationships and risk metrics) before being stored in the standardized data warehouse, eliminating the need for manual data preparation later
Solution Approach 2:
The patent transforms data from various formats and structures into a standardized parameter set. Different data sources are converted to common data models with standardized fields, data types, and relationships, enabling automated aggregation and analysis without manual intervention
3Adaptability or versatility
If organizational data is disparately stored on external and internal systems, then data can be maintained in various formats, but conventional solution systems cannot leverage and analyze this data in a secure and performant manner
Solution Approach 1:
The patent creates a universal data platform that can handle multiple data formats, sources, and analytical requirements through a single standardized interface. The system provides multi-functional capabilities including data ingestion from various sources, standardization, enrichment, storage, and analysis, thereby improving productivity while maintaining format flexibility
Data Source
AI summary
Techniques described herein include performing advanced data analytics based on disparate data sources in cloud computing environments. Cloud platform analytics system(s) associated with an organization may be implemented to retrieve organization-related data from various internal and/or external data sources. The cloud platform analytics systems may enrich and store the data within a cloud-based storage system, including structuring the data to perform specific organization management analytics. The various data analytics may be executed in the cloud environment using secure and performant analytics tools, and the results of the analytics processes may be output via reports, dashboards, notifications, and the like, to downstream systems and/or client devices.