Unified Data Correlator for IT Business Decision Support
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Solution Overview
Problem
Decision makers in IT face challenges in making informed business decisions due to scattered and isolated IT data stored across various domain-specific solutions, making it laborious to correlate and integrate relevant information.
Innovation Solution
A system comprising a business management database, configuration management database, and a data correlator that defines relationships between data from these databases, enabling the presentation of related data and supporting what-if analysis to facilitate informed IT business decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in multiple domain-specific applications and spreadsheets, then data can be organized by specific interests, but data integration and correlation become laborious and complex
Solution Approach 1:
The patent merges multiple domain-specific applications and spreadsheets into a unified data warehouse that consolidates operational, financial, and strategic data. This integration is achieved through automated ETL processes that extract data from various sources, transform it into a common format, and load it into the centralized warehouse, thereby reducing data integration complexity while maintaining organizational flexibility.
Solution Approach 2:
The data warehouse serves multiple functions simultaneously - it stores operational data from IT systems, financial data from accounting applications, and strategic data from spreadsheets. The unified platform enables various decision-making activities including financial analysis, operational monitoring, and strategic planning, making the system universally applicable across different business needs.
2Ease of operation
If data is isolated in specific silos, then data can be easily accessed for specific purposes, but correlating useful data becomes a laborious manual process
Solution Approach 1:
The system implements automated feedback mechanisms where the data warehouse continuously receives updates from operational systems, financial applications, and spreadsheets. This automated data synchronization eliminates manual correlation processes by continuously integrating new data, reducing the time required to gather and correlate information for decision-making.
Solution Approach 2:
The data warehouse acts as an intermediary layer between various data sources and decision-makers. It receives data from multiple silos, processes and correlates it automatically, and presents integrated information through unified interfaces. This intermediary function eliminates the need for manual data correlation while maintaining easy data access for users.
3Adaptability or versatility
If multiple applications and solutions are used, then specific domain requirements can be met, but data forms vary and decision maker burden increases
Solution Approach 1:
The data warehouse maintains local quality by preserving domain-specific data characteristics and formats in their original structures while storing them in a centralized location. Each domain (IT operations, finance, strategy) retains its specific data formats and structures, allowing domain experts to access familiar data representations while benefiting from unified storage and automated integration across all domains.
Data Source
AI summary
Various embodiments include methods and systems to support IT business decision making, including a data correlator and business, configuration, risk, and application management databases. The business management database contains information pertaining to services offered by IT and other IT business information. The configuration management database contains operational data including the resources required by IT's offered services. The risk management database contains operational constraints on the organization by external sources, such as industry practices or government regulations. The application management database contains information about projects and applications that are in development but not currently operational including resources required by IT's services now or in the future. The data correlator defines relationships between related data residing in one or more of the databases, allowing a single convenient location to access data useful in making business decisions for an organization's information technology department. In various embodiments the data correlator includes a what-if analyzer to model decisions and determine the impact of those decisions. In various embodiments snapshots may be taken of the configuration management database to be used later to determine the operational state at a previous time and assess changes to the configuration management database between that time and the present.