TIBCO® Data Science is a unified platform that combines the capabilities of TIBCO Statistica™, TIBCO Spotfire® Data Science (formerly Alpine Data), TIBCO Spotfire® Statistics Services, and TIBCO® Enterprise Runtime for R (TERR). TIBCO Data Science allows organizations to expand data science deployments across the organization by providing flexible authoring and deployment capabilities.
Data Science Author
Team Studio, formerly known as Spotfire Data Science (and Alpine Data Labs), Team Studio is a collaborative web based user interface that allows data scientists and citizen data scientists to create machine learning and data prep pipelines. Users can use the drag-and-drop interface and/or seamlessly integrate code via a Jupyter Notebook node. They can also use Slack-like collaboration features to accelerate data science projects.
Statistica™ provides a rich desktop based user interface that allows data scientists to create sophisticated advanced analytic workflows using 16,000 functions. Users can also seamlessly integrate Python, R, and other nodes within the pipelines. Additionally, users can create parameterized workspaces that can be invoked via Spotfire. The desktop version of Statistica will continue to be offered as a stand alone product.
TIBCO Enterprise Runtime for R (TERR) is a high-performance, enterprise-quality statistical engine to provide predictive analytic capabilities. It is available for integration into other applications through various APIs. Developing in R, and then deploying on TERR, lets you rapidly move from prototyping to production, without recoding and retesting your analyses.
Data Science Operations
Distributed services are required for Team Studio. These services take the pipelines created by Team Studio and push down all computations to the underlying big data source systems such as Spark. In addition, distributed services provide project management, collaboration, scheduling, model management, and governance.
Core services are optional and are used with Statistica. These services provide a very rich and robust set of model management, platform management, scoring, and governance capabilities for Statistica.
Ecosystem services are required for TERR. These services allow organizations to federate data science workloads across a variety of engines including SAS, MatLab, R, and Python.