Development of an Automated Data Management and Reporting System for Large-Scale Energy Modeling

The client currently manages their data using legacy systems combined with manual Excel processes, which become inadequate as data volumes grow into dozens of millions of records. This results in increased processing time, manual effort, and inefficiencies in reporting, hindering timely analysis and decision-making.

A mid-to-large size energy consulting firm specializing in sustainable energy strategies, managing extensive datasets for modeling and reporting purposes.

• Reduce data processing time from hours to minutes for large datasets containing dozens of millions of records
• Automate data transformation, integration, and report generation processes to minimize manual effort
• Implement an accessible and interactive reporting platform that accelerates report creation to under 10 minutes per document
• Enable comprehensive change management controls to ensure data and system modifications align with organizational standards
• Develop intuitive UI modules for technical staff to manage complex datasets efficiently
• Facilitate multiuser access to support collaborative data analysis and reporting

• An automated data processing component utilizing a flexible data transformation engine to handle large datasets efficiently
• Integration with cloud-based infrastructure (e.g., Azure Cloud) for scalable data storage and processing
• Connection to various data sources, such as GAMS, Excel, and other modeling tools, supporting default formats and custom uploads
• Custom UI modules within the data management platform for streamlined data upload/download and single sign-on capabilities
• A comprehensive reporting dashboard enabling dynamic filtering, flexible aggregations, and visualization through an internal analytics dashboard
• Multiuser access with role-based permissions for collaborative analysis and reporting
• Change management features to track modifications, ensure compliance, and support audit requirements

• External data sources such as GAMS, Excel, and other modeling inputs for data ingestion
• Cloud-based analytics and visualization tools for report creation and sharing
• Authentication services for SSO to streamline user access
• Existing data storage systems to facilitate seamless data transfer

• System scalability to manage data volumes expanding into tens of millions of records without performance degradation
• High availability and reliability to ensure continuous access during critical analysis periods
• Data security protocols conforming to industry standards, including role-based access control and audit logging
• Performance targets to reduce data processing and report generation time from hours to minutes
• Ease of use through a modern, intuitive user interface suitable for technical and non-technical users

The implementation of the automated, cloud-enabled data management and reporting system is expected to significantly reduce data processing times from hours to minutes, lower manual effort in report generation by up to 90%, and enhance collaborative data analysis. These improvements will enable faster decision-making, more accurate modeling, and better stakeholder communication, ultimately supporting the client's strategic sustainability goals.