Metadata-Driven Data Ingestion for Remote Computing Environments
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Solution Overview
Problem
Transitioning data from on-premises resources to remote computing environments is challenging due to the heterogeneity and complexity of data, requiring a framework that is fast, efficient, accurate, robust, modular, adaptable, and cost-effective.
Innovation Solution
A framework that extracts metadata from data files, correlates it with configuration files to determine the appropriate ingestion protocol, and uses separate configuration files for processing, allowing for modular ingestion and reducing computational effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a framework is implemented to migrate vast amounts of heterogeneous data from on-premises resources to remote computing environments, then data migration capability is improved, but device complexity increases
Solution Approach 1:
The framework is segmented into distinct functional modules: a metadata extraction module that extracts properties from incoming data files, a configuration file determination module that selects appropriate configuration files based on extracted metadata, and an ingestion module that processes files according to selected configuration. This modular architecture allows the system to handle heterogeneous data sources while maintaining manageable complexity through clear separation of concerns.
Solution Approach 2:
Configuration files serve as intermediaries between the metadata extraction process and the actual data ingestion process. These configuration files contain pre-defined parameters and settings that bridge the gap between diverse data source characteristics and the standardized ingestion requirements of the remote computing environment, eliminating the need for complex real-time decision logic.
2Productivity
If computational effort is reduced through modular ingestion protocols, then productivity is improved, but manufacturing precision may worsen
Solution Approach 1:
Configuration files are prepared in advance with all necessary ingestion parameters, validation rules, and processing instructions pre-defined. This preliminary action allows the actual data ingestion process to execute quickly without real-time computational overhead, while still maintaining high precision because the processing rules have been carefully configured beforehand based on the specific characteristics of each data source.
Data Source
AI summary
A system, device, and method for ingesting data into a remote computing environment are provided. The example device comprises a processor, a communications module, and a memory. The processor executes instructions on the memory to receive a data file, and extract metadata from the data file. The extracted metadata comprises at least one property of the data file. A configuration file, from a plurality of configuration files, that is associated with the data file is determined. The determination is performed, at least in part, based on correlating the extracted metadata with data file types used by the determined configuration file. The data file is ingested for storage in a remote computing environment based on the determined configuration file.