SAS Visual Data Science Integrations

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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.

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You can collaborate with others without ever leaving your document. Or, you can jot down an idea using your digital pen. Do you need to publish a newsletter? You can easily convert your Word document to a webpage. Collaboration with others around the world Just one click and you can translate documents into your non-native language. You can add 3D models to your document. Learn Tools allows you to easily correct any errors in your content. It's now easier to find great sources. You can use Researcher to view articles in the task pane, so you can focus on your writing. It's helpful to see the bigger picture when you're working on your document. The Editor Overview Pane allows you to find and fix any proofing problems.

SAS Visual Statistics allows multiple users to interactively explore data and then create and refine predictive models. Your statisticians and data scientists can use the most appropriate analytical modeling techniques to analyze your observations at a fine level. What will you get? The result? You can quickly build and refine models to target specific segments or groups, and run multiple scenarios simultaneously. To get better results, you can ask more "what-if" questions. You can also use an automatically generated score code to put your results into practice. Multiple users can interact with data visually. They can add, change, or remove outliers. You can instantly see how changes affect the predictive power of your model and make adjustments quickly. Data science teams have the freedom to work in the language they prefer, so they can make the most of their talents. SAS Visual Statistics combines all analytical assets.

SAS®, Viya®, data science offerings offer a comprehensive, scalable analytical environment that is quick and easy to use, allowing you to meet diverse business requirements. Automatically generated insights allow you to identify the most commonly used variables across all models, the most significant variables selected across models, and assess results for all models. Natural language generation capabilities allow you to create project summaries in plain language. This makes it easy to interpret reports. Analytics team members can add project notes and comments to the insights report to facilitate communication between team members. SAS allows you to embed open source code into an analysis and call open-source algorithms seamlessly within its environment. This allows for collaboration within your organization as users can program in the language they prefer. SAS Deep Learning with Python (DLPy) is also available on GitHub.