Domain-Specific Query Language for Investor Relations Data Analysis
Solution Overview
Problem
Current investor relations management systems lack efficient automation tools, requiring non-technical investor relations officers (IROs) to learn complex data retrieval languages or use limited graphical interfaces, hindering their ability to perform complex queries and analyze data effectively.
Innovation Solution
Development of a domain-specific query language and toolset for investor relations, allowing IROs to perform queries and generate reports using investor relations-specific terms, which are then converted to general data retrieval languages like SQL, enabling non-technical users to create complex queries and analyze data without learning SQL, and providing a client-side toolset with features like query builders and report generators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-technical IROs use general data retrieval languages like SQL, then they can perform complex queries and analyze data effectively, but they need to learn complex data retrieval languages which increases the difficulty of operation
Solution Approach 1:
The patent introduces a domain-specific query language as an intermediary layer between the user (IRO) and the underlying SQL database system. This intermediate language allows IROs to perform complex data retrieval and analysis without needing to learn SQL syntax, while still leveraging the full power of SQL for executing queries against the investor relations data store.
2Ease of operation
If a domain-specific query language is created for investor relations, then non-technical users can perform queries easily, but the system complexity increases due to language conversion and additional processing layers
Solution Approach 1:
The system implements a query translation layer that converts domain-specific investor relations queries into SQL statements. This intermediary processing layer handles the complexity of language conversion automatically, allowing users to work with simple domain-specific syntax while the system manages the translation to and from SQL, thus isolating complexity from the user interface.
3Productivity
If automated tools and services are implemented for investor relations, then productivity and efficiency improve, but the initial system complexity and development requirements increase
Solution Approach 1:
The patent segments the investor relations management system into distinct functional modules including: (1) a domain-specific query language processor, (2) a query-to-SQL translation engine, (3) a data store management system, and (4) automated reporting services. This segmentation allows each component to be developed and maintained independently, reducing overall system complexity while enabling automated tools that improve productivity.
Data Source
AI summary
Techniques to automate the management of investor relations are disclosed herein. A vertical domain query language is introduced, specifically for investor relations. Graphical query builder tools to create queries in the vertical domain query language are described. Reports specific to investor relations, in particular reports to assess the efficacy of investor relations activities, are also described. Investor relations client applications that make use of user state, such as identity, date time stamp and geolocation are described.