List of the Top 5 Data Visualization Software for SAS Viya in 2025

JMP, a data analysis tool available for both Mac and Windows, integrates robust statistical capabilities with engaging interactive visualizations. Users can effortlessly import and analyze data thanks to its drag-and-drop interface, which features dynamically linked graphics, extensive libraries of advanced analytical tools, a scripting language, and various options for sharing insights, enabling a more profound exploration of data. Founded in 1980, JMP was created to harness the emerging potential of graphical user interfaces for personal computers, and it has consistently evolved by incorporating state-of-the-art statistical techniques in each new version. Remarkably, John Sall, the founder of JMP, remains actively involved in the development of the software as its Chief Architect, ensuring that it stays at the forefront of data analysis innovation.

Employ a comprehensive set of SAS tools to access, handle, analyze, and present data in visual formats. By using SAS Visual Machine Learning, organizations can significantly boost their analytical skills through integrated machine learning and deep learning functionalities that improve visualization and reporting methods. This strategy empowers users to visually identify and reveal significant connections within their data sets. Furthermore, the platform enables the development and dissemination of interactive reports and dashboards, while also allowing for self-service analytics that quickly assess possible outcomes, encouraging more informed, data-driven decision-making. Users have the capability to explore their data deeply and build or adjust predictive models in the SAS® Viya® environment. Enhanced collaboration among data scientists, statisticians, and analysts allows for the ongoing refinement of models tailored to particular segments or demographics, ensuring that decisions are made based on accurate insights. Additionally, the user-friendly visual interface streamlines the resolution of complex analytical issues, effectively managing all aspects of the analytics lifecycle while fostering a cooperative atmosphere for all participants. This collaborative framework not only enhances the efficiency of the analytical process but also leads to more innovative and effective solutions in data interpretation.

Effectively uncover emerging trends and patterns by accessing, analyzing, and manipulating data. SAS Visual Data Science offers a comprehensive self-service platform that facilitates the creation and sharing of insightful visualizations along with interactive reports. By utilizing machine learning, text analytics, and econometric methods, users can improve forecasting and optimization abilities while managing both SAS and open-source models, whether within projects or as standalone entities. This tool is essential for visualizing relationships within data, enabling users to generate and share interactive reports and dashboards, and leveraging self-service analytics to swiftly assess potential outcomes for more informed, data-driven choices. Engage in data exploration and build or modify predictive analytical models using this integrated solution with SAS® Viya®. Promoting collaboration among data scientists, statisticians, and analysts allows teams to continuously refine models designed for specific segments or groups, resulting in decisions grounded in accurate insights. This collaborative framework not only boosts model precision but also significantly speeds up the overall decision-making process, ultimately driving better business outcomes. Additionally, the ability to quickly iterate on models fosters an environment of innovation and adaptability, ensuring that strategies remain relevant in a rapidly changing landscape.

We are excited to present a comprehensive and user-friendly suite that facilitates data access, manipulation, analysis, and visualization, available for both cloud and on-premises environments. Why continue to manage multiple software systems from different vendors? Our integrated package includes three of our most popular offerings—Base SAS, SAS/STAT, and SAS/GRAPH—reducing costs associated with licensing, maintenance, training, and support while providing consistent access to information across your organization. Our SAS statistical methods are routinely updated to reflect the most current advancements in statistical science. Furthermore, our technical support team is composed of experienced statisticians holding master's and doctorate degrees, delivering a level of expertise and service that is seldom found among software providers. With over four decades of experience in developing statistical analysis tools, SAS remains the preferred option for organizations worldwide seeking dependable solutions for their data challenges. This ongoing dedication to quality ensures that you have the necessary tools to make well-informed decisions driven by precise data insights. By choosing SAS, you are investing in a future where data-driven strategies can thrive.

An intuitive low-code visual platform enables users to create and deploy customized chatbots that comprehend natural language effectively. Users can obtain text responses, access data, create reports and visualizations, and apply analytics and AI through an easy-to-navigate conversational interface. Integrated within the SAS ecosystem, the platform allows seamless configuration of bots to improve data insight accessibility or connect them to external services for enhanced reach. Gaining insights from data has never been easier than just sending a straightforward message. With the aid of intelligent suggestions and clearly labeled related metrics, users can swiftly pinpoint significant relationships within their data. By harnessing machine learning and natural language explanations, users can discover, visualize, and convey engaging narratives and insights that are both accessible and comprehensible. This allows for a deep investigation into the causes behind various outcomes, exploration of all potential avenues, and the unearthing of hidden opportunities within the data. Moreover, the system automatically identifies key relationships, outliers, clusters, and more, revealing vital insights that can inform strategic actions and decision-making. Ultimately, this groundbreaking approach equips users with the tools to confidently and clearly navigate through intricate data environments and make impactful decisions based on their findings.