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ease
features
design
support

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Description

SAS Enterprise Guide provides users with a streamlined way to harness the analytical capabilities of SAS via a user-friendly point-and-click interface designed for Windows. This tool enables users to independently conduct analyses by merging a vast selection of analytical options with SAS software's robust features, all within an intuitive graphical interface. Consequently, business analysts can generate their own insights and disseminate reports, allowing IT departments to concentrate on more strategic initiatives. Furthermore, SAS Enterprise Guide seamlessly integrates with SAS Viya, enabling teams to utilize their existing workflows while executing SAS programs in the cloud without the need for recoding, thus leveraging the advantages of a modern, cloud-based environment that offers increased efficiency, scalability, and enhanced analytical capabilities. Additionally, it assists users in quickly accessing data for their analyses, scheduling projects, sharing outcomes, and embedding outputs for recurring use, which includes leveraging advanced analytics and various other functionalities provided by SAS. This combination of features not only enhances productivity but also fosters a more collaborative approach to data analysis within organizations.

Description

Utilize a robust suite of SAS technologies to access, manipulate, analyze, and present information through visual formats. By leveraging SAS Visual Machine Learning, organizations can enhance their analytical capabilities with integrated machine learning and deep learning features, which facilitate improved visualization and reporting practices. This approach allows users to visualize and uncover pertinent relationships within their data. Additionally, the platform supports the creation and sharing of interactive reports and dashboards, alongside enabling self-service analytics to swiftly evaluate potential outcomes, fostering smarter, data-driven decisions. Users can delve into their data and construct or modify predictive analytical models while operating within the SAS® Viya® environment. Collaborative efforts among data scientists, statisticians, and analysts enable iterative model refinement tailored to specific segments or groups, ensuring decisions are informed by precise insights. Moreover, this comprehensive visual interface simplifies the resolution of intricate analytical challenges, efficiently managing every aspect of the analytics lifecycle while promoting a more collaborative environment for all stakeholders involved.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

SAS Viya
Microsoft 365
Microsoft Excel
Microsoft Outlook
Microsoft PowerPoint
Microsoft Word
SAS Visual Statistics

Integrations

SAS Viya
Microsoft 365
Microsoft Excel
Microsoft Outlook
Microsoft PowerPoint
Microsoft Word
SAS Visual Statistics

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

SAS

Founded

1976

Country

United States

Website

www.sas.com/en_us/software/enterprise-guide.html

Vendor Details

Company Name

SAS

Country

United States

Website

support.sas.com/en/software/visual-machine-learning.html

Product Features

Data Analysis

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

Product Features

Data Visualization

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

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives