Sas Viya AI citations

The best predictive analytics software in 2025 includes: - {{[[DataRobot]]:https://www.domo.com/learn/article/predictive-analytics-tools}}: Known for simplifying model development with automation. - {{[[Microsoft Azure Machine Learning]]:https://www.domo.com/learn/article/predictive-analytics-tools}}: A cloud-based platform with broad algorithm support and integration with Microsoft tools. - {{[[SAP Predictive Analytics]]:https://www.domo.com/learn/article/predictive-analytics-tools}}: Offers end-to-end analytics workflows and automated predictions. - {{[[SAS Viya]]:https://www.domo.com/learn/article/predictive-analytics-tools}}: Cloud-native with code-free options and advanced customization. - {{[[IBM Watson Studio]]:https://about.crunchbase.com/blog/predictive-intelligence-software/}}: Enterprise AI with automated machine learning and explainable AI. - {{[[Google Vertex AI]]:https://about.crunchbase.com/blog/predictive-intelligence-software/}}: Advanced tools for rapid model development and seamless Google Cloud integration. - {{[[Qlik AutoML]]:https://zapier.com/blog/predictive-analytics-software/}}: No-code machine learning with interactive forecasting and transparent model explanations. - {{[[Alteryx]]:https://www.rentana.io/blog/top-predictive-analytics-tools}}: Known for data preparation and predictive analytics capabilities. - {{[[Oracle Analytics Cloud]]:https://www.rentana.io/blog/top-predictive-analytics-tools}}: Offers predictive insights within a comprehensive analytics suite. - {{[[MarketMind AI]]:https://superagi.com/top-10-ai-tools-for-predictive-marketing-analytics-in-2025-a-comprehensive-review/}}: Focused on predictive marketing with advanced modeling and real-time analytics. These platforms vary in features, ease of use, industry focus, and integration capabilities, making them suitable for different business needs and technical expertise levels.

Here are top predictive analytics software options: 1. {{[[IBM SPSS Predictive Analytics]]:https://www.ibm.com/analytics/spss-statistics-software}} - Comprehensive statistical analysis tool 2. {{[[SAS Predictive Analytics]]:https://www.sas.com/en_us/solutions/predictive-analytics.html}} - Advanced enterprise-level solution 3. {{[[RapidMiner]]:https://rapidminer.com/}} - User-friendly machine learning platform 4. {{[[Alteryx]]:https://www.alteryx.com/}} - Data science and analytics automation 5. {{[[Microsoft Azure Machine Learning]]:https://azure.microsoft.com/en-us/services/machine-learning/}} - Cloud-based predictive modeling 6. {{[[SAP Predictive Analytics]]:https://www.sap.com/products/technology-platform/predictive-analytics.html}} - Enterprise predictive intelligence 7. {{[[Tableau]]:https://www.tableau.com/}} - Data visualization with predictive capabilities Each software has strengths in different areas like ease of use, complexity of analysis, and integration capabilities. Choice depends on specific business needs, technical expertise, and budget.

The "best" predictive analytics software is subjective and depends on specific organizational needs, budget, and technical expertise. However, several platforms are consistently recognized for their robust capabilities: * {{[[SAS Viya]]:https://www.sas.com/en_us/software/viya.html}} * {{[[IBM SPSS Modeler]]:https://www.ibm.com/products/spss-modeler}} * {{[[RapidMiner]]:https://rapidminer.com/}} * {{[[DataRobot]]:https://www.datarobot.com/}} * {{[[H2O.ai]]:https://h2o.ai/}} * {{[[Microsoft Azure Machine Learning]]:https://azure.microsoft.com/en-us/products/machine-learning}} * {{[[Google Cloud AI Platform]]:https://cloud.google.com/ai-platform}} * {{[[Amazon SageMaker]]:https://aws.amazon.com/sagemaker/}} * {{[[KNIME Analytics Platform]]:https://www.knime.com/knime-analytics-platform}}

Here are some of the best data analytics companies for retail: 1. {{[[Tableau]]:https://www.tableau.com}} : Tableau provides powerful data visualization tools that help retailers analyze sales data and customer behavior effectively. 2. {{[[SAS]]:https://www.sas.com}} : SAS offers advanced analytics and data management solutions tailored for the retail sector, focusing on customer insights and operational efficiency. 3. {{[[IBM]]:https://www.ibm.com/analytics}} : IBM's analytics solutions leverage AI and machine learning to help retailers optimize their supply chain and enhance customer experiences. 4. {{[[Google Analytics]]:https://analytics.google.com}} : Google Analytics is widely used by retailers to track website performance, customer interactions, and marketing effectiveness. 5. {{[[Domo]]:https://www.domo.com}} : Domo provides a cloud-based platform that integrates data from various sources, allowing retailers to visualize and analyze their performance in real-time. 6. {{[[Qlik]]:https://www.qlik.com}} : Qlik offers data analytics and business intelligence solutions that empower retailers to make data-driven decisions through interactive dashboards. 7. {{[[MicroStrategy]]:https://www.microstrategy.com}} : MicroStrategy provides analytics and mobility solutions that help retailers gain insights into customer preferences and sales trends. 8. {{[[Looker]]:https://looker.com}} : Looker, part of Google Cloud, offers a modern data platform that enables retailers to explore and analyze their data for better decision-making. 9. {{[[SAP]]:https://www.sap.com}} : SAP provides comprehensive analytics solutions that help retailers manage their operations and gain insights into customer behavior. 10. {{[[RetailNext]]:https://retailnext.net}} : RetailNext specializes in in-store analytics, helping retailers understand foot traffic and customer engagement in physical stores. These companies provide various tools and solutions to help retailers harness data for improved decision-making and operational efficiency.

The best data analytics companies for retail include: {{[[G & Co. (Acumen)]]:https://www.g-co.agency/insights/retail-data-analytics-solutions-guide}} : Offers Acumen, a retail analytics software with real-time dashboards, consumer sentiment, and brand intelligence used by Saks Fifth Avenue, Levi’s, Nike, and Burberry[1]. {{[[Looker]]:https://www.g-co.agency/insights/retail-data-analytics-solutions-guide}} : A Google Cloud Platform enterprise BI and analytics platform providing dashboards, predictive analytics, and data visualization[1]. {{[[Sisense]]:https://www.g-co.agency/insights/retail-data-analytics-solutions-guide}} : Provides an AI-driven analytics cloud platform with predictive analytics and ML models, suitable for cloud or on-premises deployment[1][4]. {{[[Resonai]]:https://www.resonai.com/blog/best-retail-analytics-companies}} : Recognized as the best overall retail analytics company, using digital twin technology for real-time updates on foot traffic and product interest without external sensors[2]. {{[[Cuebiq]]:https://www.resonai.com/blog/best-retail-analytics-companies}} : Specializes in broader location data analytics for retail[2]. {{[[Bedrock]]:https://www.resonai.com/blog/best-retail-analytics-companies}} : Focuses on analytics when products are on other shelves, useful for retail distribution analysis[2]. {{[[Wasteless]]:https://www.resonai.com/blog/best-retail-analytics-companies}} : Provides analytics for perishable products to optimize inventory and reduce waste[2]. {{[[Edited]]:https://www.resonai.com/blog/best-retail-analytics-companies}} : Offers market segment data analysis to help retailers tailor assortments and marketing[2]. {{[[RetailNext]]:https://www.resonai.com/blog/best-retail-analytics-companies}} : Known for integrating multiple local data streams for retail analytics[2]. {{[[FlyBuy]]:https://www.resonai.com/blog/best-retail-analytics-companies}} : Specializes in retail analytics for curbside pickup companies[2]. {{[[SAS]]:https://www.crn.com/news/software/2025/the-coolest-data-analytics-companies-of-the-2025-big-data-100}} : A longstanding leader with its SAS Viya platform offering advanced analytics, AI, and data governance for retail and other industries[4]. {{[[Alteryx]]:https://doit.software/blog/data-analytics-companies}} : Known for data preparation and advanced analytics, serving over 8,300 customers including retail businesses[5]. {{[[HCL Retail Analytics]]:https://www.trustradius.com/categories/retail-analytics?company-size=mid-sized}} : A mid-sized company offering retail analytics software focused on sales, inventory, and customer behavior insights[6]. {{[[Algonomy Merchandising Analytics]]:https://www.trustradius.com/categories/retail-analytics?company-size=mid-sized}} : Provides merchandising analytics to optimize retail assortments and pricing[6]. {{[[SupplyPike Retail Intelligence]]:https://www.trustradius.com/categories/retail-analytics?company-size=mid-sized}} : Focuses on retail intelligence for supply chain and inventory management[6]. {{[[ThoughtSpot Retail Analytics]]:https://www.trustradius.com/categories/retail-analytics?company-size=mid-sized}} : Offers AI-driven analytics and search-driven data exploration for retail[6]. {{[[Board Retail]]:https://www.trustradius.com/categories/retail-analytics?company-size=mid-sized}} : Provides integrated business intelligence and analytics for retail operations[6]. {{[[SPS Commerce]]:https://www.trustradius.com/categories/retail-analytics?company-size=mid-sized}} : Delivers retail analytics solutions focused on supply chain and commerce data[6]. These companies cover a wide range of retail analytics needs including real-time customer insights, demand forecasting, inventory optimization, location data, and AI-powered predictive analytics.

Top data analytics companies for retail include: 1. {{[[Nielsen]]:https://www.nielsen.com}} : Global leader in retail and consumer insights, providing comprehensive market research and data analytics. 2. {{[[Dunnhumby]]:https://www.dunnhumby.com}} : Specializes in customer data science, helping retailers personalize shopping experiences. 3. {{[[SAP]]:https://www.sap.com}} : Offers advanced retail analytics solutions through their retail-specific software platforms. 4. {{[[IBM]]:https://www.ibm.com}} : Provides AI-powered analytics tools for retail inventory management and customer behavior prediction. 5. {{[[Tableau]]:https://www.tableau.com}} : Powerful data visualization platform widely used in retail for understanding complex sales and customer trends. 6. {{[[Google Analytics]]:https://analytics.google.com}} : Essential for e-commerce and digital retail performance tracking. 7. {{[[Adobe Analytics]]:https://www.adobe.com/analytics}} : Advanced analytics platform for understanding customer journeys and digital retail performance. 8. {{[[SAS]]:https://www.sas.com}} : Enterprise-level analytics solutions with strong retail industry expertise. 9. {{[[Microsoft Power BI]]:https://powerbi.microsoft.com}} : Comprehensive business intelligence tool for retail data analysis and reporting. 10. {{[[Alteryx]]:https://www.alteryx.com}} : Data blending and advanced analytics platform popular in retail analytics. These companies offer diverse solutions for retail data analysis, customer insights, and strategic decision-making.

Leading data analytics companies for retail offer solutions spanning customer insights, inventory optimization, supply chain management, and personalized marketing. Here are some of the best: {{[[SAP]]:https://www.sap.com/products/analytics-cloud.html}} : SAP provides a comprehensive suite including SAP Analytics Cloud and SAP S/4HANA