The Team Studio Environment
The Team Studio environment was built to facilitate the analytics process at all levels of the business, from defining a problem to driving business action. The collaborative user interface in Team Studio allows cross-functional teams to work together on data science projects and build machine-learning workflows using a web interface and a minimum of code, while leveraging big-data platforms.
Each component of the application focuses on a different task.
- Glossary
TIBCO® Data Science Team Studio defines certain product-related terms and uses them in the user interface and in the documentation. Understanding the meaning of these terms can help you to work in Team Studio. - Workspaces
Workspaces are self-contained projects within Team Studio. You can add data sets and files, invite others to collaborate, and share progress. You can also build and run analytic workflows and notebooks within the workspace. - Workflows
Model your analytics process with a directed graph of operators called a workflow. Workflows combine data sources and operators (algorithms and transformations). - Touchpoints
Data scientists and engineers can use touchpoints to create user-friendly applications that harness Team Studio analytic workflows without any programming. Front-line business users can then use these interactive self-service tools to get the answers they need, when they need them. - Search
To search Team Studio objects by name, provide the name of a dataset, workspace, or user in the Search box. Accessing the search function from this field automatically defaults to Search in All and Show All Results. - Tags
Tags are keywords or labels that can be assigned to items in Team Studio. Tags provide a mechanism for identifying and informally categorizing material in the application. - Jupyter Notebooks
You can integrate Jupyter Notebooks running Python code with Team Studio.
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