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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 Invenis?
Invenis is a powerful platform designed for data analysis and mining, which allows users to efficiently clean, aggregate, and analyze their data while scaling their operations to improve decision-making. It provides an array of functionalities, including data harmonization, preparation, cleansing, enrichment, and aggregation, as well as advanced predictive analytics, segmentation, and recommendation tools. By seamlessly integrating with multiple data sources such as MySQL, Oracle, Postgres SQL, and HDFS (Hadoop), Invenis enables thorough analysis of various file formats, such as CSV and JSON. Users can create predictions across all datasets without needing coding abilities or a specialized team, as the platform smartly chooses the most effective algorithms based on the specific data characteristics and intended use cases. Moreover, Invenis streamlines repetitive tasks and regular analyses, allowing users to save significant time and fully harness their data's potential. The platform also promotes collaboration by enabling teams to work together—not just among analysts but across different departments—thus facilitating smoother decision-making processes and ensuring that information circulates efficiently throughout the organization. This approach ultimately empowers businesses to make well-informed decisions based on timely and precise data insights, fostering a culture of data-driven decision-making that can adapt to evolving market dynamics. By leveraging these capabilities, organizations can enhance their overall efficiency and competitiveness in their respective industries.
Media
No images available
Integrations Supported
Hadoop
MySQL
Oracle Cloud Infrastructure
PostgreSQL
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
Invenis
Company Location
France
Company Website
invenis.co/en/logiciel/
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
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
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery