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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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

Financial institutions increasingly require advanced software solutions to effectively utilize the vast amounts of data they gather regarding their services and customer interactions. This software must be capable of real-time data analysis to uncover correlations and recognize emerging trends. Additionally, it should generate comprehensive reports and visual representations of these complex analyses, which can assist the bank's leadership in making informed decisions. By analyzing all services available through the bank's active retail channels, targeted marketing strategies can be crafted, such as providing tailored value-added services that enhance the overall customer experience. To help banks maximize the potential of their extensive data and develop a thorough understanding of the information crucial for strategic insights, Auriga has introduced the WWS BAM (Business Analytics Management) system, which streamlines the analytics process and empowers decision-makers with actionable intelligence. This innovative approach not only enhances operational efficiency but also positions banks to adapt swiftly to market changes and customer preferences.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

SAS Viya Yes 

Integrations

SAS Viya No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

SAS

Founded

1976

Country

United States

Website

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

Vendor Details

Company Name

Auriga

Country

United States

Website

www.aurigaspa.com/en/banking/products-and-solutions/business-analytics/wws-business-analytics-management/

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Product Features

Data Analysis

Data Discovery No 
Data Visualization No 
High Volume Processing No 
Predictive Analytics No 
Regression Analysis No 
Sentiment Analysis No 
Statistical Modeling No 
Text Analytics No 

Alternatives

Alternatives