Configurable Data Ingestion With Automated Error Remediation
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Solution Overview
Problem
Managing data ingestion from non-traditional sources is inefficient and resource-intensive, requiring significant time and resources, especially in handling user authentication, data preprocessing, and error remediation.
Innovation Solution
A system and method for data ingestion that includes authentication, preprocessing, API data processing, postprocessing, and failure response, utilizing a server device with modules for authentication, preprocessing, data processing, and failure response, and employing REST API, GraphQL, and Splunk mechanisms for efficient data ingestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If customized tools and significant resources are used to handle data ingestion, then data ingestion can be performed with proper security and user management, but the process becomes time-consuming and resource-intensive
Solution Approach 1:
The patent implements a universal data ingestion framework that can handle multiple data sources, formats, and security requirements through a single standardized system. The framework provides configurable authentication mechanisms, template-based processing, and automated error handling that work across diverse data ingestion scenarios, eliminating the need for customized tools for each specific case while maintaining proper security controls
Solution Approach 2:
The system performs preliminary actions by pre-configuring authentication mechanisms, validation rules, and error handling procedures before data ingestion begins. Configuration files define processing parameters in advance, and the framework pre-establishes security protocols and user access controls, allowing data to be ingested immediately upon arrival without time-consuming setup or manual configuration during the ingestion process
2Reliability
If significant resources are allocated to data ingestion processes, then proper user management and security can be maintained, but resource efficiency decreases
Solution Approach 1:
The data ingestion framework implements self-service mechanisms where the system automatically authenticates users, validates data against predefined schemas, detects and remedies errors, and manages the entire ingestion process without requiring significant manual resource allocation. The configurable framework self-adapts to different data sources and formats, eliminating the need for extensive manual configuration and monitoring resources
Solution Approach 2:
The system optimizes resource usage by dynamically adjusting processing parameters based on data characteristics, volume, and priority. Configuration files allow flexible parameter adjustment for different ingestion scenarios, enabling the system to allocate resources efficiently rather than using fixed high-resource configurations for all cases, thus maintaining security while reducing overall resource consumption
3Adaptability or versatility
If manual processes are used for data ingestion, then flexibility in handling different data sources can be maintained, but processing speed and efficiency decrease
Solution Approach 1:
The patent segments the data ingestion process into distinct, modular components including authentication, data extraction, validation, error handling, and loading. Each component can be independently configured through configuration files to handle different data sources and formats, providing flexibility while enabling automated processing. This segmentation allows the system to adapt to various data sources through configuration rather than manual process design, significantly improving efficiency
Data Source
AI summary
An example computer system for ingestion of data can include: one or more processors; and non-transitory computer-readable storage media encoding instructions which, when executed by the one or more processors, causes the computer system to: authenticate a user to allow for definition of a configuration file for the ingestion of the data; receive the configuration file, with the configuration file defining parameters for the ingestion of the data; extract the data through an application programming interface according to the parameters of the configuration file; and perform remediation on an error record in the data according to an error code associated with the error record.