Interactive Report UI for Linked Database Table Selection
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Solution Overview
Problem
Conventional user interfaces for report generation from database tables are inefficient, requiring technical knowledge to identify and join related tables and shared data fields, leading to limited and time-consuming report creation.
Innovation Solution
An improved user interface automatically identifies and displays related database tables and shared data fields, allowing users to generate reports without prior knowledge of the underlying database structure, enhancing user experience and flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional user interfaces are used for report generation, then users can create reports from database tables, but users require technical knowledge to identify and join related tables and shared data fields, making the process time-consuming and limited
Solution Approach 1:
The system automatically identifies related database tables and shared data fields without requiring user intervention. The processor performs automated table relationship detection and data field matching, allowing the system to serve itself by eliminating the need for users to possess technical database knowledge.
Solution Approach 2:
The system acts as an intermediary between the user and the complex database structure. By automatically handling table joins and data field identification, the system mediates the interaction, shielding users from technical complexity while still enabling report generation from multiple related tables.
2Productivity
If automated identification of related tables and shared data fields is implemented, then report generation becomes more efficient and intuitive, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-identifying and storing information about related database tables and shared data fields. This preliminary processing enables rapid report generation subsequently, as the complex analysis work is done in advance and cached for future use.
Solution Approach 2:
The patent replaces manual mechanical processes (users manually identifying and joining tables) with automated computational processes. The processor automatically performs table relationship detection and data field matching, substituting human cognitive and manual operations with algorithmic processing.
3Adaptability or versatility
If users manually write programs to generate reports, then custom reports can be created, but significant processing and memory resources are consumed
Solution Approach 1:
The system provides a universal interface that handles multiple report generation tasks through a single automated process. Rather than requiring separate programs for different reports, the system universally applies automated table and field identification across all report generation requests, reducing redundant processing.
Solution Approach 2:
The system creates and reuses templates or cached structures of table relationships and data field mappings. Once the complex relationship structure is identified, it is copied and reused for subsequent report generations, avoiding repeated full analysis and reducing processing resource consumption.
Data Source
AI summary
Certain aspects of the disclosure provide a method of constructing a report incorporating data stored in a plurality of database tables. The method generally includes receiving, via an interactive user interface (UI), a selection of a first database table, generating a visualization of data associated with the first database table organized in rows and columns, wherein each column includes data for a data field in the first database table, displaying, via the interactive UI, shared data fields associated with other related database tables and shared among all of the other database tables, receiving, via the interactive UI, a selection of a first shared data field, and displaying, via the interactive UI, data for the first shared data field from all the other database tables in a first new column added to the visualization, wherein each row in the first new column includes data from one of the other database table.


