Amazon QuickSight generative BI enables Solomon’s actionable transformation toward net zero

This is a guest post written by Randy Toombs of HSB Solomon Associates LLC.

HSB Solomon Associates LLC (Solomon) is a global leader in benchmarking and performance improvement for the oil and gas industry. Solomon provides data-driven, strategic insight across the energy industry, leading to greater efficiency, reliability, and profitability for our clients.

In this post, we share how Solomon used Amazon QuickSight and AWS technologies to transform emissions data analysis in the oil and gas industry, reducing analysis time from 6 weeks to just 1 week while providing real-time insights for sustainable operations.

Industry challenge

Oil and gas operators, financial institutions, and stakeholders face significant challenges in developing achievable sustainability targets, mitigating risk, and estimating CO2-equivalent (CO2e) emissions across their portfolios. The complexities involved in acquiring accurate asset-level emissions data are compounded by diverse operational practices, technologies, and regulatory environments. Traditional tools like Microsoft Excel and legacy database systems resulted in time-consuming manual processes, while the lack of standardized methodologies for measuring and reporting emissions led to inconsistencies and transparency concerns. The previous process required 3 weeks to complete using manual calculations. Afterward, it took an additional 2 weeks to prepare the data for review and export into third-party file formats. By implementing QuickSight and Amazon Relational Database Service (Amazon RDS), the entire process was streamlined and reduced to just 4–5 days. With QuickSight, users can now build, filter, and export portfolio assets in minutes. The data visualization capabilities of QuickSight have eliminated the need for manual data uploads and complex formula management in Excel, greatly enhancing efficiency for clients.

Solution overview

To address these challenges, Solomon developed the Oil and Gas Carbon Emissions Solution, powered by QuickSight, Amazon Bedrock, and Amazon Q. The solution uses publicly available data and standardized models to provide insight into asset-level carbon emissions for 98.5% of global oil and gas production, including consistent, global comparisons of emissions across different assets, regions, and companies.

The following diagram illustrates the solution architecture.

The carbon emissions data processing pipeline uses the advanced AWS Cloud infrastructure to deliver efficiency, scalability, and user-centric insights. Initially, raw carbon emissions data is imported into the system using Amazon API Gateway, providing secure and seamless data ingestion. This data is subsequently loaded into the RDS database, which serves as the central computational hub. Amazon RDS is optimized for running complex equations and analytical processes, offering computational speed and accuracy significantly superior to traditional tools like Microsoft Excel. These capabilities enable the handling of extensive datasets with reduced processing time and enhanced reliability.

After the calculations are performed, the results are stored in structured tables within Amazon RDS. These outcomes are then visualized through QuickSight, a robust business intelligence (BI) tool capable of managing over a million data points. QuickSight allows users to drill down into the data, exploring granular insights through interactive dashboards. Additionally, QuickSight is integrated with the Carbon Emissions Application using AWS Lambda, which hosts and executes web applications efficiently without requiring dedicated server management. Lambda provides a serverless architecture that enhances application scalability, resilience, and cost-effectiveness.

To augment the depth of data insights, Amazon Q in QuickSight integrates with Amazon Bedrock, incorporating scientific research knowledge bases into the analytical framework. This synergy between Amazon RDS data and Amazon Bedrock knowledge bases allows for the generation of advanced reports that combine empirical data with domain-specific scientific context.

Users benefit from a Natural Query Language (NQL) bar embedded in the application, which facilitates the creation of personalized metrics and charts tailored to individual needs. These custom visualizations are securely saved and associated with the logged-in user, providing a personalized and interactive data exploration experience. This comprehensive system demonstrates how AWS services collaboratively enable advanced data analysis, security, and user-centric functionality for the Carbon Emissions Application.

Advanced security and access management

Cybersecurity was paramount in the development of this tool. Solomon used the comprehensive security infrastructure of AWS to incorporate multilayered authentication protocols, encrypted data storage, and stringent access controls. Access control for the application is enforced using AWS Identity and Access Management (IAM), which defines user permissions and provides secure authentication. The application further integrates Amazon Cognito to support client-specific single sign-on (SSO) protocols, offering flexibility for users to either use their own security models or adopt the Carbon Emissions Application’s default Amazon Cognito based authentication.

Real-world impact and visualization

The Oil and Gas Carbon Emissions Solution has transformed how companies manage and reduce their carbon footprint. The dashboard (as shown in the following screenshot) enables users to quickly identify high-emission assets and implement targeted management strategies through its drill-down capabilities. The portfolio management feature allows users to construct and assess portfolios of assets, providing a comprehensive view of CO2e emission risks.

Business benefits

The implementation of this AWS powered solution has delivered significant benefits:

• Reduced emissions data analysis time from 6 weeks to 1 week
• Enabled real-time visualization and analysis at both macro and micro levels
• Standardized emissions reporting for consistent global comparisons
• Enhanced security and access control through AWS services
• Cost-effective scaling through the QuickSight user-based pricing model
• Process enhancement from data calculation to visualization improved by 80%
• Using QuickSight saves clients over $14,000 per year as compared to other visualization applications
• Clients build the portfolio of oil and gas assets in minutes as compared to months of manual research

Conclusion

We continue to expand the dashboard’s capabilities, incorporating additional KPIs for broader sustainability insights and enhancing predictive analytics through Amazon Bedrock. This will allow users to interact with internal and external libraries for more in-depth analysis, further supporting the oil and gas industry’s journey toward net-zero emissions.

The success of this implementation demonstrates how cloud-based analytics can address complex industry challenges while supporting critical sustainability goals. Through the combination of AWS technologies and Solomon’s industry expertise, we’re helping transform how the oil and gas sector approaches emissions management and sustainability planning.

Learn more about how QuickSight can help transform your organization’s data analytics capabilities by visiting the Amazon QuickSight User Guide.

About the Author

Randy Toombs, Director of Application Development at HSB Solomon Associates LLC, is an experienced leader in the energy and government sector with a focus on IT business development and strategy utilizing artificial intelligence. His expertise spans multiple facets of the energy industry and government, and his work demonstrates a deep understanding of market dynamics and operational efficiencies.