Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Eighty percent of the data you possess includes a spatial aspect, and leveraging this can greatly enhance your decision-making processes. By utilizing the spatial dimension, you can visualize your data on a map almost instantly, allowing you to recognize location-based phenomena more effectively. Enhance your analysis by incorporating spatial elements to gain a deeper understanding of your operations within their broader context, which can help uncover emerging trends. You can also test various hypotheses, such as evaluating the establishment of a new location, planning sector divisions, or reorganizing logistics. This approach enables you to weigh different options more effectively and make informed decisions. Furthermore, you can present your analyses and decisions in a manner that suits your requirements, utilizing high-definition maps, automated reports, dynamic dashboards, or interactive self-service tools, ensuring that your insights are accessible and actionable. By adapting your presentation methods, you can facilitate better communication and collaboration within your team and stakeholders.
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
No
API Access
Has API
Yes
Integrations
Microsoft 365
No
Microsoft Excel
No
Microsoft Outlook
No
Microsoft PowerPoint
No
Microsoft Word
No
SAS Visual Statistics
No
SAS Viya
No
Integrations
Microsoft 365
Yes
Microsoft Excel
Yes
Microsoft Outlook
Yes
Microsoft PowerPoint
Yes
Microsoft Word
Yes
SAS Visual Statistics
Yes
SAS Viya
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
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
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Articque
Founded
1989
Country
France
Website
www.articque.com
Vendor Details
Company Name
SAS
Country
United States
Website
support.sas.com/en/software/visual-machine-learning.html
Product Features
Location Intelligence
Behavioral Analytics
No
Data Visualization
Yes
Demographic Data
Yes
Geocoding
Yes
Geofencing
No
Location Tracking
No
Predictive Analytics
Yes
Trade Area Analysis
Yes
Product Features
Data Visualization
Analytics
No
Content Management
No
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No