Best Data Visualization Software for SAS Viya

JMP, data analysis software Mac and Windows, combines powerful statistics with interactive visualization. It is simple to import and process data. Drag-and-drop interface, dynamically linked graphics, libraries of advanced analytics functionality, scripting language, and ways to share findings with others allow users to dig deeper into their data with greater ease. JMP was originally developed in 1980 to capture the new value of GUI for personal computers. JMP continues to add cutting-edge statistical methods to the software's functionality with every release. John Sall, the organization's founder, is still Chief Architect.

SAS technologies combine to provide powerful tools for visual information. You can access, manipulate, analyze, and present information in visual formats. SAS Visual Machine Learning allows you to expand your analytics by using machine learning and deep learning capabilities. This makes it easier to visualize and report better. Visualize and discover relationships in your data. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes to make data-driven, smarter decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions. A comprehensive visual interface allows you to solve complex analytical problems. It handles all aspects of the analytics lifecycle.

Access, explore, and prepare data while discovering new patterns and trends. SAS Visual Data Science allows you to create and share interactive visualizations and reports using a single interface. It uses machine learning, text analysis, and econometrics to improve forecasting and optimization. Additionally, it registers SAS and open source models within projects and as standalone models. Visualize your data and find relevant relationships. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes for better, data-driven decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions.

A powerful, yet simple-to-use package for accessing, manipulating and analyzing information. Now available for cloud or on-site deployment. Why combine niche software packages from different vendors. A consolidated portfolio, which includes three of our most popular products (Base SAS, SAS/STAT, and SAS/GRAPH), reduces licensing, maintenance, and training costs, while providing consistent information across your enterprise. SAS statistical procedures are continuously updated to reflect the most recent advances in statistical methodology. Technical support is provided by highly qualified statisticians at master's and doctorate levels. This allows them to provide a level of service that is not possible with other software vendors. SAS has over four decades of experience in developing statistical analysis software that organizations around world rely upon to provide accurate answers for data questions.

A low-code visual interface allows you to create and deploy natural language chatbots. You can access data, reports, visualizations, and text responses. You can even apply analytics and AI using a natural language, conversational interface. You can connect to external services or configure bots within SAS to get more insights. Sending a message is all it takes to get insights from your data. Using suggestions and clearly identified related actions, you can quickly spot important relationships within your data. Machine learning and natural language explanations can be used to create stories and insights that are simple to understand and explain. Examine all options, find the reasons for what happened, and discover hidden opportunities in your data. Automately highlight key relationships, outliers and clusters to uncover vital insights that can inspire action.