Database Reporting System Using Project Keys and Templates
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Solution Overview
Problem
Retrieving and extracting related data from large databases is challenging due to data being stored in different locations and formats, leading to inefficient processing and resource consumption, which degrades system performance.
Innovation Solution
The system uses project keys and report templates to efficiently identify and extract data by tracking related data records and generating personalized reports, reducing the search space and processing resources needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If an exhaustive search is performed to identify related information in large databases, then completeness of data retrieval is improved, but processing resources consumed increases significantly and system performance degrades
Solution Approach 1:
The patent segments the large database search space into smaller, manageable units by organizing data into hierarchical structures (e.g., projects, tasks, components). Instead of searching the entire database exhaustively, the system divides the search into targeted segments based on user needs and data relationships, reducing the overall processing burden while maintaining retrieval completeness.
Solution Approach 2:
The system performs preliminary actions by pre-processing and organizing database data into structured formats with defined relationships and metadata before search operations. This includes creating indexes, establishing data hierarchies, and pre-identifying related records, so that when a search is initiated, the system can quickly navigate to relevant data without exhaustive scanning.
2Loss of information
If all data is extracted from data records to ensure complete information retrieval, then information completeness is improved, but processing power and network resources consumed increase significantly
Solution Approach 1:
The patent applies extraction by selectively retrieving only the specific data elements and records that are relevant to the user's query or report requirements. Instead of extracting all data from data records, the system identifies and extracts only the necessary portions based on predefined criteria, data relationships, and user preferences, significantly reducing processing and network resource consumption.
Solution Approach 2:
The system applies local quality by customizing data extraction based on specific user needs, report types, and contextual requirements. Different users or report templates receive different subsets of data elements tailored to their specific purposes, rather than uniformly extracting all data from all records. This localized approach optimizes resource usage by extracting only what is necessary for each specific output.
3Loss of information
If large amounts of data are extracted from data records to ensure complete information, then information completeness is improved, but latency increases and system throughput decreases
Solution Approach 1:
The system selectively extracts only the necessary data elements required to fulfill the specific report or query requirements, rather than extracting large amounts of unnecessary data. This targeted extraction approach maintains information completeness for the requested output while minimizing the volume of data processed, thereby reducing latency and preserving system throughput.
4Loss of information
If data records in different formats and locations are searched to identify related information, then data coverage is improved, but search complexity increases
Solution Approach 1:
The patent implements universality by creating a unified search interface and processing framework that can handle multiple data formats, locations, and structures through a single system. The system provides universal data access mechanisms that translate various data formats and locations into a common processing model, allowing comprehensive data coverage without increasing search complexity for the user.
Solution Approach 2:
The system introduces intermediary layers such as data translation services, format conversion mechanisms, and unified access protocols that mediate between diverse data sources and the search functionality. These intermediaries handle the complexity of different formats and locations transparently, allowing the search system to maintain simplicity while achieving comprehensive data coverage.
Data Source
AI summary
A database reporting device that includes a network interface in signal communication with a database. The network device further includes a processor configured to receive a report request comprising a project key and to identify data records associated with the project key. The processor is further configured to identify a report template for a user associated with the report request and to identify data record element types corresponding with sections of the identified report template. The processor is further configured to generate a search query for data record elements corresponding with the identified data record element types and to send the search query to the database. The network device is further configured to receive a plurality of data record elements, to populate the report template with data record elements that correspond with data record element types for each section, and to output a report based on the populated report template.