Query Date Term Granularity Interface
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Solution Overview
Problem
Users of business management software face inefficiencies when trying to modify query results or change the output format, as they must switch between query designer components and re-run queries, making real-time adjustments cumbersome.
Innovation Solution
The introduction of modules that provide an interface for adding date term granularity to query results, allowing users to modify queries without re-programming, by classifying date fields, computing additional time periods, and appending these to the query, enabling real-time restructuring and formatting of query outputs through a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users modify query results by returning to the query designer to change the query, then the query can be restructured and re-executed, but the process becomes cumbersome and inefficient requiring switching between components
Solution Approach 1:
The patent introduces an intermediary layer between the static query and the visual output. This intermediary enables real-time modifications to query results through visual interfaces without requiring users to return to the query designer. The intermediary processes visual modifications and translates them into query result adjustments, eliminating the need for component switching while maintaining query restructuring capability.
Solution Approach 2:
The patent transforms the static query execution model into a dynamic interaction model. Instead of executing a query once and displaying fixed results, the system allows real-time modifications to query criteria, grouping, and formatting through visual interfaces. The query execution becomes an iterative, dynamic process where users can adjust results immediately without re-configuring the original query, significantly improving operational efficiency.
2Reliability
If users re-run queries to get updated results after modifications, then the query results are refreshed, but time is lost during the re-execution process
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing query results in a structured format that can be dynamically modified. Instead of executing the complete query from scratch each time, the system has prepared the foundational query structure and data retrieval mechanisms in advance. When users make modifications through the visual interface, the system only needs to adjust parameters and re-execute relevant portions, significantly reducing the time required compared to complete re-execution.
3Measurement precision
If the system provides detailed date term granularity options, then users can precisely control time period breakdowns, but the query complexity and processing requirements increase
Solution Approach 1:
The patent applies segmentation by breaking down the date field into multiple hierarchical levels (e.g., year, quarter, month, week, day). Instead of requiring users to manually construct complex date queries, the system pre-segments the date field into manageable time period categories. Users can selectively apply different granularities through the visual interface, and the system automatically handles the complexity of date arithmetic and grouping, providing precise control without increasing query structure complexity.
Data Source
AI summary
Additional date term granularity may be added to query results and query interfaces used to append query results. Initially, a partial execution of a query may be triggered to identify fields and field types. Fields may be classified as date fields based on their field type. The query may be appended to compute one or more time periods for each classified date field. Each time period may identify a broader time period than the data included in a corresponding classified date field. A query result, which may include the computed time period(s) and time period field(s), may be generated from the execution of the appended query.