Past Project
Posit Implementation – Oil & Gas (Marketing & Risk)
The marketing and risk function in the client’s downstream energy business had reached a ceiling with spreadsheets and legacy tools. Analysts needed faster, more flexible ways to model exposures, run scenarios, and test trading strategies. Existing workflows relied heavily on Excel, which was brittle, slow to scale, and hard to govern across a growing team. The group wanted to adopt open-source analytics in R and Python, but the company had no infrastructure to support those languages securely. Without enterprise environments, standardized packages, or deployment controls, IT could not allow the group to move forward. The absence of a formal platform created both a capability gap and a barrier to innovation.
The project established Posit (formerly RStudio) as the enterprise environment for statistical computing and model deployment. The engagement was technical in nature, focusing on infrastructure, security, and integration rather than business-side model design. A Posit Workbench cluster was deployed in a secure cloud environment, configured to support both R and Python development. Containerized environments were introduced, giving analysts access to consistent, pre-approved packages and eliminating dependency conflicts.
Posit Connect provided the distribution layer, allowing analysts to publish applications, dashboards, and APIs into a governed space. Access controls were tied into the company’s identity management system, ensuring that sensitive market and risk data could only be used by authorized groups. Logging, monitoring, and audit trails were enabled from day one, giving IT the ability to manage the platform at enterprise scale. The result was a production-grade environment where the marketing and risk team could finally build, test, and deploy advanced analytics with confidence.
Solution
Key Features
The solution delivered a fully containerized development and deployment stack for R and Python. Analysts could work in standardized environments while IT maintained central oversight of package versions and system libraries. Integration with Active Directory provided role-based access, while Posit Connect gave users a secure channel to share applications and reports across the business. Monitoring and log aggregation allowed proactive management of usage, performance, and compliance. The platform balanced flexibility for end users with the governance required by enterprise IT.
Outcomes
Enterprise-grade Posit environment deployed to support R and Python analytics
Secure containerized environments with standardized package management
Centralized governance of user access, logging, and monitoring
Analysts able to build and publish dashboards and APIs in a supported platform
Elimination of spreadsheet bottlenecks and manual data wrangling
A scalable foundation for future advanced analytics in trading and risk management
Business Drivers
The initiative was driven by the need to modernize analytical capabilities in the marketing and risk function. Spreadsheets had become a bottleneck, unable to handle the scale or speed required for trading and exposure analysis. The business wanted to empower analysts to use R and Python without compromising on security. IT needed a supported platform that could be deployed and maintained consistently across the enterprise. Leadership sought to create a foundation that would enable advanced analytics in the future, starting with a secure and scalable environment today.
Technologies
The solution centred on Posit Workbench and Posit Connect as the core platform components. Containerization was delivered through Docker and orchestrated with Kubernetes, providing resilience and scalability. Active Directory handled authentication and authorization, while TLS and network segmentation secured communication.
Observability was established with Splunk and Azure Monitor for log management and performance tracking. Together, this stack enabled the organization to introduce R and Python analytics in a way that satisfied both business demand and IT governance.