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What is WizWhy?

WizWhy examines the interplay between the values of one data field and those of others within the dataset. This analysis revolves around a user-selected dependent variable, while the other fields serve as independent variables or conditions. The dependent variable can be analyzed in two distinct ways: either as a Boolean value or as a continuous measurement. To enhance their analysis, users can fine-tune various parameters, such as the minimum probability needed for rule generation, the minimum number of instances required to substantiate each rule, and the relative costs of false negatives compared to false positives. WizWhy effectively identifies and articulates a set of rules that link the dependent variable to the other fields, employing if-then and if-and-only-if statements to convey these relationships. Furthermore, based on the established rules, WizWhy reveals significant patterns, uncovers unexpected rules that may highlight intriguing phenomena, and identifies anomalies within the dataset. In addition to this, WizWhy can also generate predictions for new instances by utilizing the rules it has derived, enabling users to make informed decisions based on the analysis. The comprehensive insights provided by WizWhy empower users to understand their data more deeply and leverage the findings for strategic purposes.

What is PROSPER?

Introduced in the early 1990s, PROSPER has experienced over two decades of ongoing research and development. Each year, it receives upgrades that introduce new models and features, expanding upon its already extensive functionality. With a capability to simulate more than three million combinations, it effectively models a variety of physical phenomena found in wells and pipelines. Notably, the adaptive interface intelligently restricts the user's view to only the relevant fields and menus based on their inputs, making the model-building experience more streamlined. PROSPER has established itself as the industry standard for well and pipeline modeling, owing to its robust technical foundation and unique modeling capabilities. Presently, it is integral to the Digital Oil Field system, where its calculation engine supports numerous real-time workflows across hundreds of fields worldwide. Consequently, users from various locations reap the benefits of its sophisticated features, reinforcing its status as a vital resource in the oil and gas industry. This evolution demonstrates how PROSPER continues to adapt to the changing demands of the sector while maintaining its leading position.

Media

No images available

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

WizSoft

Date Founded

1983

Company Location

United States

Company Website

www.wizsoft.com/products/wizwhy/

Company Facts

Organization Name

Petroleum Experts

Date Founded

1990

Company Location

Scotland

Company Website

www.petex.com/products/ipm-suite/prosper/

Categories and Features

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Data Mining

Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining

Predictive Analytics

AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

Categories and Features

Oil and Gas

Compliance Management
Equipment Management
Inventory Management
Job Costing
Logistics Management
Maintenance Management
Material Management
Project Management
Resource Management
Scheduling
Work Order Management

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