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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.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
Red Hat OpenShift
SAS Analytics for IoT
SAS Data Science Programming
SAS Visual Data Science
SAS Visual Data Science Decisioning
SAS Visual Machine Learning
SAS Viya

Integrations Supported

Motion Array

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Linux

Supported Platforms

SaaS
Windows
Mac

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

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

Not specified

Statistical Analysis

Not specified

Categories and Features

Artificial Intelligence

Machine Learning
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Business Intelligence

Data Analysis
Predictive Analytics
Visual Analytics

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