08 / 2019

TIBCO Data Science – Team Studio 6.5

Expanded Cloud Data Source Connectivity:

  • Azure SQL Data Warehouse
  • Google BigQuery
  • Oushu 3.1
  • Cloudera 6
  • Google DataProc
  • Greenplum Database 5

Running Python in Jupyter Notebooks for Team Studio on JupyterHub

You can now run the Python engine as a local managed process in Jupyter Notebooks for Team Studio, in addition to running it in a Docker container.

Integration with TIBCO Statistica

TIBCO Statistica™ workflow files (*.sdm) are now recognized and filterable through the Workfile browser.

Additional Operators


Takes an HDFS dataset in stacked format and produces an unstacked (wide) HDFS dataset using user-specified grouping and pivot columns.

Line Chart

Produces a line chart for a user-specified X-axis and Y-axis, and aggregates the values in the Y-axis.

Generalized Linear Regression Models

Fits a regression model to predict a dependent variable that follows some distribution from the exponential family of distributions.

11 / 2018

TIBCO Data Science

Available on AWS Marketplace and combining the capabilities of TIBCO Statistica™, TIBCO Spotfire® Data Science (formerly Alpine Data), and TIBCO® Enterprise Runtime for R (TERR) in a single unified platform, TIBCO Data Science extends team collaboration, automation, common metadata, project management, and model operations.

Innovation and collaboration capabilities

  • Easily spin up big data sandboxes in the AWS cloud
  • Get accelerated performance with Spark Node Fusion that chains Hadoop operations to process workflows in half the time or less
  • Use new operators and algorithms: rename and reorder columns; use Chi Square tests, categorical encoding for using non-numerical features in algorithms, and sessionization for identifying user sessions in log files; store common words and phrases in reference documents; edit and run multiple workflows simultaneously; export to FTP, Spotfire, and Excel; and much more

05 / 2018

TIBCO Statistica™ 13.4

With the release of this new version, it’s even easier to deploy sophisticated analytic models to real-time scoring environments and empower citizen data scientists:

  • Integrate with TIBCO Spotfire® to run Statistica workspaces via Spotfire® data functions
  • Access data from Spotfire by importing a Spotfire workspace node (.sbdf) and exporting data back to Spotfire
  • Reuse Spotfire data connections by accessing them directly from a workspace
  • Publish PMML models to TIBCO StreamBase® streaming analytics, which uses the TIBCO® Artifact Management Server
  • Use Elasticsearch text analytics to process unstructured data
  • Use support of OSI PI event frames and asset framework data
  • Use more analytics, including Lasso regression (feature selection method) and dynamic time warping to align IoT sensor data