On-Demand SAP Data Ingestion Across Cloud Environments
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Solution Overview
Problem
Traditional business data handling architectures are inflexible and require custom configuration and programming to provide SAP data to specific cloud storage environments, workforce accessible applications, and machine learning services, limiting real-time and batch data access.
Innovation Solution
An on-demand data ingestion system using OData API on REST protocol enables flexible, real-time and batch data access to SAP data without custom software, supporting various cloud environments and applications through a fee-per-use model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional business data handling architectures are used, then data access is secured and structured, but flexibility and adaptability are limited requiring custom configuration and programming
Solution Approach 1:
The patent implements a universal data access platform that provides standardized interfaces for accessing SAP data across multiple cloud environments and application types. The system includes pre-configured connection templates and data extraction frameworks that work with various cloud providers (AWS, Azure, Google Cloud) and application categories (BI, analytics, mobile) without requiring custom configuration for each scenario, thereby achieving multi-functionality while reducing complexity
Solution Approach 2:
The system enables self-service data access by providing automated data extraction, transformation, and loading processes that occur without manual intervention. The platform automatically handles data provisioning, security configuration, and performance optimization based on predefined policies and metadata, allowing users to access data through simple high-level interfaces rather than complex custom programming
2Productivity
If custom software and programming are used to provision data, then specific data needs can be met, but operational costs and time consumption increase
Solution Approach 1:
The patent implements preliminary action by pre-configuring data extraction templates, transformation rules, and loading processes before data access is needed. The system includes pre-built connection frameworks to various cloud environments and application types, along with predefined data mapping configurations, so that when data access is required, the infrastructure is already in place and ready for immediate use without time-consuming setup
Solution Approach 2:
The system uses copying by creating standardized templates and frameworks that can be rapidly instantiated for different data access scenarios. Instead of building custom solutions from scratch, the platform provides reusable templates for data extraction, transformation, and loading that can be copied and adapted to various needs, significantly reducing configuration time and operational costs
3Reliability
If traditional architectures are used, then system security is maintained, but real-time data access to multiple cloud environments is not enabled
Solution Approach 1:
The patent introduces an intermediary layer that acts as a secure bridge between SAP systems and various cloud environments. This intermediary platform handles data extraction, transformation, and loading while maintaining security controls, enabling reliable data access to multiple cloud providers without compromising system security. The intermediary manages authentication, authorization, and data encryption throughout the data flow
4Ease of manufacture
If fee-per-use model is implemented, then operational costs are reduced, but infrastructure complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the data access infrastructure into modular, independently manageable components. The system is segmented into data extraction modules, transformation modules, loading modules, and cloud environment connectors, each of which can be independently configured, monitored, and scaled. This modular architecture enables cost-efficient resource allocation where only the necessary components are activated for each data access scenario, reducing overall infrastructure complexity while maintaining cost efficiency
Data Source
AI summary
Disclosed herein is novel system and method for business data handling technology that provides on-demand access to business data and provisioning the business data flexibly for use by multiple applications, and for storage to multiple cloud environments. In exemplary embodiments, the system comprises an on-demand data ingestion service module and a service agent existing independently from the remaining entrenched architectural elements of a business information system architecture.