SAS Visual Data Science, now known as SAS Viya Advanced, is a comprehensive analytics platform designed to empower users in accessing, exploring, and preparing data through a unified, self-service interface. It facilitates the creation and sharing of interactive reports and dashboards, enabling users to uncover patterns and insights without requiring advanced analytical skills. The platform integrates machine learning, text analytics, and econometrics capabilities to enhance forecasting and optimization processes. Additionally, it supports the management and registration of both SAS and open-source models, either within projects or as standalone entities. Key Features and Functionality: - Data Access and Preparation: Users can import data, join tables, and manage datasets seamlessly, facilitating efficient data preparation. - Visual Data Exploration: The platform offers web-based exploratory analysis, allowing users to visually discover data insights and create interactive reports and dashboards. - Self-Service Analytics: Users can develop and deploy analytical models without extensive coding, leveraging machine learning algorithms such as decision forests. - Text Analysis: Gain sentiment and insights from text data through integrated text analytics capabilities. - Model Development and Deployment: The platform supports the entire analytical lifecycle, from data preparation and exploration to model development and deployment, accommodating multiple personas within the same integrated environment. - Open Source Integration: It integrates with open-source tools and languages, including Python, R, Java, and Lua, allowing users to build models using their preferred programming languages. Primary Value and User Solutions: SAS Viya Advanced addresses the need for a unified analytics environment that simplifies the data science process. By providing a self-service interface, it enables users across various skill levels to access, prepare, and analyze data efficiently. The integration of machine learning and text analytics enhances forecasting and optimization, leading to more informed decision-making. Furthermore, the platform's support for both SAS and open-source models ensures flexibility and scalability, catering to diverse analytical requirements.