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What is SAS Visual Statistics?
SAS Visual Statistics fosters collaborative data exploration, allowing multiple users to interactively create and refine predictive models. Data scientists and statisticians can apply the most appropriate analytical techniques to derive insights at an intricate level. As a result, insights can be discovered at impressive speeds, leading to new revenue growth opportunities. This platform permits the construction and optimization of models targeted at specific demographics or segments, while simultaneously exploring various scenarios. Such capabilities motivate users to raise numerous what-if questions to improve outcomes. Moreover, results can be operationalized through automatically generated score code, streamlining application processes. Users can visually manipulate the data by adding or modifying variables, removing outliers, and more, which enables them to instantly evaluate how changes affect the model's predictive accuracy, facilitating rapid adjustments. Data science teams benefit from the flexibility of working in their preferred programming languages, thereby maximizing their skill set. Ultimately, SAS Visual Statistics unifies all analytical resources into a holistic solution for data-driven decision-making. This integration creates an environment that nurtures innovation and expands the horizons of data analysis, enabling teams to push the limits of their analytical capabilities. Furthermore, the collaborative features of the platform enhance teamwork and knowledge sharing among users, driving better results through collective expertise.
What is DAVinCI LABS?
In the process of selecting a target for prediction, a sophisticated algorithm discerns patterns within the dataset to construct a forecasting model. By identifying a variable that acts as a basis for decision-making, it systematically organizes clusters that display significant trends and defines the characteristics of each cluster through established rules. Furthermore, if the features of the data change over time, it can project future target values by analyzing trends associated with the time variable. Even when the characteristics of the data are not explicitly stated, the algorithm skillfully categorizes clusters with distinct behaviors, which can aid in identifying outliers in new datasets or offer novel insights. In our company's method for identifying marketing targets, we consider variables such as gender, age, and mortgage status; however, it may be advantageous to investigate additional factors that could improve our predictive performance. By incorporating elements like income level, education, and geographic location, we could further enhance our targeting strategy and ensure that our marketing efforts are more effectively aligned with potential customers' needs. This comprehensive approach to data analysis could ultimately lead to better decision-making and increased success in our campaigns.
Integrations Supported
Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
Motion Array
Red Hat OpenShift
SAS Analytics for IoT
SAS Data Science Programming
SAS Visual Data Science
SAS Visual Data Science Decisioning
SAS Visual Machine Learning
Integrations Supported
Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
Motion Array
Red Hat OpenShift
SAS Analytics for IoT
SAS Data Science Programming
SAS Visual Data Science
SAS Visual Data Science Decisioning
SAS Visual Machine Learning
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
SAS
Company Location
United States
Company Website
www.sas.com/en_us/software/visual-statistics.html
Company Facts
Organization Name
AILYS
Company Location
South Korea
Company Website
davincilabs.ai
Categories and Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Statistical Analysis
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization
Categories and Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics