Automated Data Pipeline for Diverse File Type Parsing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The complexity and cost of analyzing data from various formats and sources hinder accurate and efficient data analytics, as existing systems require manual processing and lack automation for handling diverse file types and irrelevant data.
Innovation Solution
A data processing system that automatically identifies file types, uses parsers associated with regular expressions to extract relevant data, transforms data into standardized formats, and creates pipelines for analysis, while monitoring for errors and notifying users, enabling automated data manipulation and error management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing is used to handle diverse file types and formats, then data analysis accuracy can be maintained through careful review, but productivity is significantly reduced and costs increase
Solution Approach 1:
The patent segments the data processing workflow into distinct automated components: file type identification, parser selection, data extraction, transformation, and validation. Each component handles specific tasks independently, enabling automated processing while maintaining quality control through structured validation rules
Solution Approach 2:
The system automatically adjusts processing parameters based on file type identification. Different parsers and transformation rules are applied depending on the detected file format, enabling efficient automated processing of diverse data sources while maintaining accuracy through parameter-specific validation
2Productivity
If automated processing is implemented to handle diverse file types, then productivity and efficiency are improved, but device complexity increases due to multiple parsers and transformation rules
Solution Approach 1:
The patent implements a universal data processing platform that handles multiple file types through a common architecture. The system uses a unified interface for file ingestion, automatic file type detection, and dynamic parser selection, allowing a single system to process diverse data formats without requiring separate processing pipelines for each format
Solution Approach 2:
The system introduces intermediary components including a file type identification layer that mediates between raw file input and specific parsers, and a transformation layer that mediates between extracted data and the final standardized format. These intermediaries simplify the overall system architecture by providing standardized interfaces that decouple the complexity of handling multiple formats from the core processing logic
3Reliability
If comprehensive data validation and error monitoring are implemented, then data quality and reliability are improved, but processing time and computational resources are consumed
Solution Approach 1:
The patent implements preliminary validation checks during the data extraction and transformation phases. Validation rules are applied immediately when data is extracted from each file type, identifying and flagging errors early in the processing pipeline before they propagate to subsequent stages, thereby ensuring data quality without requiring extensive post-processing validation
Solution Approach 2:
The system incorporates feedback mechanisms where validation results from processed files inform the processing of subsequent files. Error patterns detected in one file type can trigger adaptive validation rules for similar formats, and processing metrics are used to optimize resource allocation dynamically, balancing thorough validation with efficient processing time
Data Source
AI summary
Systems and methods for transforming and pipelining data are disclosed. For example, it may be desirable to parse out usable data and to transform the usable data found in files that may be received from different sources and that may be in different file types. Described herein are system and methods that provide functionality to allow for determining a file type of a file, parsing out usable data from the file, performing a series of transformations on the usable data, and generating a pipeline that includes the series of transformations. The pipeline may be monitored for error detection.