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What is SAS Visual Analytics?

An intuitive low-code visual platform enables users to create and deploy customized chatbots that comprehend natural language effectively. Users can obtain text responses, access data, create reports and visualizations, and apply analytics and AI through an easy-to-navigate conversational interface. Integrated within the SAS ecosystem, the platform allows seamless configuration of bots to improve data insight accessibility or connect them to external services for enhanced reach. Gaining insights from data has never been easier than just sending a straightforward message. With the aid of intelligent suggestions and clearly labeled related metrics, users can swiftly pinpoint significant relationships within their data. By harnessing machine learning and natural language explanations, users can discover, visualize, and convey engaging narratives and insights that are both accessible and comprehensible. This allows for a deep investigation into the causes behind various outcomes, exploration of all potential avenues, and the unearthing of hidden opportunities within the data. Moreover, the system automatically identifies key relationships, outliers, clusters, and more, revealing vital insights that can inform strategic actions and decision-making. Ultimately, this groundbreaking approach equips users with the tools to confidently and clearly navigate through intricate data environments and make impactful decisions based on their findings.

What is RATH?

RATH transcends conventional data analysis and visualization tools such as Tableau by streamlining the exploratory data analysis process. Utilizing an advanced Augmented Analytic engine, it identifies patterns, insights, and causal relationships, delivering these findings through sophisticated, automatically generated multidimensional visualizations. This innovative approach not only enhances efficiency but also empowers users to make data-driven decisions with greater clarity and confidence.

Media

Media

Integrations Supported

Airtable
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Hive
Apache Kylin
ClickHouse
Google Cloud Platform
Impala
JMP Statistical Software
Microsoft Azure
MySQL
PostgreSQL
Red Hat OpenShift
SAS Viya

Integrations Supported

Airtable
Amazon Athena
Amazon Redshift
Amazon Web Services (AWS)
Apache Hive
Apache Kylin
ClickHouse
Google Cloud Platform
Impala
JMP Statistical Software
Microsoft Azure
MySQL
PostgreSQL
Red Hat OpenShift
SAS Viya

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

Date Founded

1976

Company Location

United States

Company Website

www.sas.com/en_us/software/visual-analytics.html

Company Facts

Organization Name

Kanaries Data

Date Founded

2019

Company Website

kanaries.org

Categories and Features

Data Analysis

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

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Categories and Features

Data Analysis

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

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

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