Altair Analytics Workbench® is a versatile, visual, multi-language integrated development environment that unifies the SAS language, Python, R, and SQL into a single tool. It offers a sophisticated coding environment for developing models and programs, supporting multi-language coding without the need for third-party licenses or software. This platform provides the fastest route to incorporating open-source tools into existing SAS language environments, enabling users to extract, transform, and analyze data from various sources efficiently. Key Features: - Robust Coding Environment: A modern IDE that allows users to create, maintain, and run programs, focusing on SAS language and Python programming, while seamlessly integrating SQL and R code. - Visual Workflow Environment: Interactive drag-and-drop blocks enable users to build workflows for data retrieval, blending, preparation, and machine learning model development without writing code. - Data Access and Preparation: Access virtually any data source, including cloud services, Hadoop, data warehouses, databases, and various file formats, with tools to clean, filter, and enrich data. - Data Exploration: Advanced tools for data profiling, graphing, and decision trees facilitate insights into complex datasets. - Local and Remote Processing: Develop and run models and programs on various infrastructures, including cloud, on-premises, and hybrid environments. Primary Value and Solutions: Altair Analytics Workbench empowers users of all skill levels by providing a unified platform for data connection, preparation, discovery, and modeling. It eliminates the need for multiple toolsets, thereby reducing costs and improving productivity. The platform allows organizations to maintain existing SAS language programs while seamlessly integrating open-source components, bridging the gap between traditional and modern analytics environments. By offering both visual workflows for non-coders and a sophisticated coding environment for experts, it addresses the diverse needs of data engineers, analysts, and scientists, facilitating efficient and collaborative data analysis processes.