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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 WizRule?

WizRule is a sophisticated data-auditing tool that automatically identifies patterns within datasets and highlights instances that stray from these norms as potential frauds or errors. Any instance that raises suspicion is one that significantly diverges from the recognized patterns established by the software. This tool is invaluable for auditors, fraud examiners, forensic investigators, and data-quality managers, whose primary objective is to detect fraudulent activities and data discrepancies. WizRule enhances their ability to achieve this goal effectively. As a data-auditing software leveraging advanced data mining techniques, WizRule conducts thorough analyses to pinpoint inconsistencies within the data. The operation of WizRule is seamless; the user only needs to select the dataset for examination, and the software takes care of the analysis. It explores all interrelationships among the various fields and highlights any unusual or improbable cases. By doing so, WizRule uncovers fraudulent activities that traditional auditing methods may overlook, ensuring a more comprehensive review of the data. Its automated nature not only saves time but also increases accuracy in identifying potential issues.

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

one time licensing fee
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

WizSoft

Date Founded

1983

Company Location

Israel

Company Website

www.wizsoft.com/wizrule/

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

Audit

Alerts / Notifications
Audit Planning
Compliance Management
Dashboard
Exceptions Management
Forms Management
Issue Management
Mobile Access
Multi-Year Planning
Risk Assessment
Workflow Management

Fraud Detection

Access Security Management
Check Fraud Monitoring
Custom Fraud Parameters
For Banking
For Crypto
For Insurance Industry
For eCommerce
Internal Fraud Monitoring
Investigator Notes
Pattern Recognition
Transaction Approval

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