Cegal Prizm documentation#
Cegal Prizm represents an easy to configure, modular solution that allows users to integrate data from different geo-applications, data sources and platforms into a single Python environment. Prizm can connect into Petrel, OSDU, and other 3rd party applications and domains to access and retrieve energy data that can then be combined for advance data analysis, plotting, data science workflows, and machine learning techniques. Users can seamlessly transfer data locally, on-prem or across hybrid deployments to a common Python environment to generate more insight and value by enriching datasets with additional application meta-data.
Convert domain data objects into common Python data structures (Pandas DataFrame or NumPy array) and seamlessly work across the Python ecosystem to drive innovation and maximize value from data.
Solve problems that are not possible with legacy applications
Integrate modern AI/ML Python technologies to extend, accelerate and augment standard workflows
Create and securely distribute customized code, services and technology to a user community for consumption
Combine data from different application silos for enriched investigation
Elevate critical analysis and support better business decisions
Secure collaborative environments for data scientists, data engineers and domain experts to share and publish Python scripts, Notebooks and ideas
Vendor and cloud agnostic solution
Be more creative and generate more insight from your geo-science data