Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Cegal Prizm is a flexible solution crafted to facilitate the seamless integration of data from various geo-applications, data sources, and platforms within a Python ecosystem. Its modular structure enables users to merge geo-data sources for sophisticated analysis, visualization, data science workflows, and machine learning applications. This innovation empowers users to tackle challenges that were previously unmanageable with older systems. By incorporating contemporary Python technologies, you can enhance, speed up, and improve standard workflows while creating and securely sharing tailored code, services, and technologies with a user community for their use. Furthermore, it connects effortlessly with the E&P software platform Petrel, OSDU, and various third-party applications and domains, allowing for the access and retrieval of energy data. Data can be transferred smoothly, whether locally or across hybrid and cloud environments, into a unified Python setting to derive greater insights and added value. Additionally, Prizm enables the enhancement of datasets with supplementary application metadata, thereby providing more depth and context to your analytical processes. The ability to customize and share these enriched datasets among users fosters collaboration and innovation within the community.
Description
Machine learning reveals concealed patterns and valuable insights within enterprise data, ultimately adding significant value to businesses. Oracle Machine Learning streamlines the process of creating and deploying machine learning models for data scientists by minimizing data movement, incorporating AutoML technology, and facilitating easier deployment. Productivity for data scientists and developers is enhanced while the learning curve is shortened through the use of user-friendly Apache Zeppelin notebook technology based on open source. These notebooks accommodate SQL, PL/SQL, Python, and markdown interpreters tailored for Oracle Autonomous Database, enabling users to utilize their preferred programming languages when building models. Additionally, a no-code interface that leverages AutoML on Autonomous Database enhances accessibility for both data scientists and non-expert users, allowing them to harness powerful in-database algorithms for tasks like classification and regression. Furthermore, data scientists benefit from seamless model deployment through the integrated Oracle Machine Learning AutoML User Interface, ensuring a smoother transition from model development to application. This comprehensive approach not only boosts efficiency but also democratizes machine learning capabilities across the organization.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Apache Hive
No
Apache Spark
No
Impala
No
Kinetica
No
MySQL
No
Oracle Cloud Infrastructure
No
Oracle Database
No
Petrel
Yes
PwC Check-In
No
Python
Yes
Integrations
Apache Hive
Yes
Apache Spark
Yes
Impala
Yes
Kinetica
Yes
MySQL
Yes
Oracle Cloud Infrastructure
Yes
Oracle Database
Yes
Petrel
No
PwC Check-In
Yes
Python
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Cegal
Founded
2000
Country
Norway
Website
www.cegal.com/en/software/data-science-and-cegal-prizm
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/data-science/machine-learning/
Product Features
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No
Oil and Gas
Compliance Management
No
Equipment Management
No
Inventory Management
No
Job Costing
No
Logistics Management
No
Maintenance Management
No
Material Management
No
Project Management
No
Resource Management
No
Scheduling
No
Work Order Management
No
Product Features
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No