Today's challenge is to blend the data between a Teradata Aster database and a KNIME table in the KNIME Analytics Platform. Why these two? Teradata Aster is a database system in use at many companies around the world, and KNIME tables are an easy way to store and access models built in other KNIME workflows. The data is from a collection of open-source heart disease data sets available in .txt format. They are available at http://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/ . This workflow was developed at Teradata using open-source data; however, the authors of the data have requested that any publications resulting from the use of the data include the names of the principle investigator responsible for the data collection at each institution. They are: 1. Hungarian Institute of Cardiology. Budapest: Andras Janosi, M.D. 2. University Hospital, Zurich, Switzerland: William Steinbrunn, M.D. 3. University Hospital, Basel, Switzerland: Matthias Pfisterer, M.D. 4. V.A. Medical Center, Long Beach and Cleveland Clinic Foundation: Robert Detrano, M.D., Ph.D. ... and yes! They blend.
EXAMPLES Server: 01_Data_Access/02_Databases/09_Teradata_Aster_meets_KNIME_Table01_Data_Access/02_Databases/09_Teradata_Aster_meets_KNIME_Table*
Download a zip-archive
- Will They Blend? Experiments in Data & Tool Blending. Today: Teradata Aster meets KNIME Table. What is that chest pain?
* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually