Data Science


Changing Metadata Classification Values When Uploading Data Files

When uploading a data file, you can view the recommended metadata classification values for each character-valued column. You can choose to keep the recommended values, or to change them.

Including classification values in your data improves the accuracy of mapping column tables correctly to each other. This is useful if you are integrating data from multiple sources, or if integrating data into a system with a predefined hierarchy. When creating unions from different data sources, the metadata classification algorithm will match columns with similar data.

Running Predictive Analytics On Your Data

When creating a Data Flow, you can easily run predictive analytics on your data sets using Machine Learning functions, without prior knowledge of advanced statistics.

Train and run multiple iterations of predictive models in parallel, evaluate and compare models actively, and select which model you want to save. Then you can re-run your model against new data sets.

Note: To use the Machine Learning feature, binaries must be installed.

Video: How to Run Predictive Data Analytics

When creating a Data Flow, you can easily run predictive analytics on your data sets using Machine Learning functions, without having prior knowledge of advanced statistics.

From the side panel, click Models.

The Regression panel opens, and displays the following regression model algorithms:

•    K-Nearest-Neighbors
•    Polynomial
•    Random Forest
•    and Extended Gradient Boosting

Drag and drop a model onto the workflow canvas.