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SAS Viya Software

star star star star star 0.0 (0 reviews) | Analytics Tools & Software · Analytics Software Platforms and Tools

Unlock the power of data with SAS Viya, a cloud-based analytics platform that supports advanced analytics and AI for fast, informed decision-making.

Product Overview

SAS Viya software enhances your data journey through a cloud-centric analytics platform tailored for adaptability and effectiveness. Although its browser-based interface may have limitations in flexibility, SAS Viya stands out as a robust analytics solution. With a user-friendly layout, it facilitates advanced analytics, artificial intelligence, and integration across multiple languages, allowing for rapid, data-informed decision-making.

Product Details
Analytics Tools & Software Features
cancel Dashboard
cancel Live Chat
cancel Reporting
cancel Automation
cancel Mobile App
cancel SSL security
cancel Geo-analytics
cancel Time Tracking
check_circle KPI Monitoring
cancel SEO management
cancel Budgeting Tools
cancel CRM Integration
cancel Email marketing
cancel Funnel Analysis
cancel Lead Management
Pros & Cons
Pros
checkComprehensive analytics platform
checkEfficient large dataset handling
checkSupports multi-language analytics work
checkAdvanced AI and machine learning tools
Cons
closeBrowser-based access lacks flexibility
closeAdvanced functionalities are complex, according to some software users
closeData visualization needs simplicity
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Frequently Asked Questions
Yes, SAS Viya software offers an API.
Yes, SAS Viya software has a mobile app designed for Android and iOS users.
SAS Viya software supports multiple languages, including English, French, German, Spanish, Japanese, Korean, and Chinese.
SAS Viya cost is not publicly available on its official website. Contact for pricing according to your business requirements.
SAS Viya software integrates with Google BigQuery, Google Chrome, Microsoft Edge, Greenplum, Amazon Redshift, Hadoop, and Mozilla Firefox.
SAS Viya software is typically used by professionals such as business analysts, MLOps engineers, data scientists, and data engineers. It serves various industries, including life sciences, banking, retail and consumer goods, manufacturing, agriculture, insurance, oil and gas, telecom, media and technology, health care, and the public sector.
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