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Data Management

Data Management features include creating and maintaining the data sources. For more information, refer to the following topics:

Data Sources

Data source is a configuration explaining from where to pull the data and how much data to pull for the model execution. The jobs user runs in PRL use data that derive from data sources. A data source can be used as input data source or output data source by a job. Predictive learning enables a data scientist to consume data from multiple data storages by providing below data sources:

  • Integrated Data Lake (IDL)
    • A reference to the folders in IDL helps models to access the data to read and write to IDL.
  • Internet of Things (IoT)
    • A configuration to read the timeseries data from an Asset.

Example of Data Sources Page

Here is an example of the Data Sources Page that illustrates some of the actions you can take with data sources:

Data-Sources-Page

Creating a Data Source

Follow these steps to create a data source:

  1. Click "Add Data Source" in the Data Management section.
  2. Select a data source location, and click "Next".
  3. Enter a name for the data source.
  4. For IoT, select the number of hours, and click "browse" to select an asset and aspect or, for IDL, select the folder and file.
  5. Click "Save".

Actions Available for All Data Sources

All data sources allow users to:

Search for a data source—enter a data source name in the search bar at the top of the Data Sources table . Only data source names can be searched. As you enter search characters, the UI displays the Data Source locations that contain files with matching names. You must click the Data Source location to expand it and view the actual files.

Last update: July 17, 2024

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