Use the AutoPrep Snap to prepare data for analysis, reporting, and machine learning without writing expressions, SQL scripts, or Python code. When you open AutoPrep, it uses introspection on a sample of the input data and calculates the probable data type and valid null handling for each field. The Preview data table shows a sample of the data it will output.
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Flatten leaf nodes of hierarchical data structures
Remove fields
Rename fields
Change the data type of String, Date, Integer, Number, and Boolean fields
Handle null values
Mask data to protect sensitive dataChange Date objects or Data Strings to Date Strings with the selected date format information
Choose the format for dates, currency, phone numbers, and country codes
Split fields based on a delimiter to create new fields
The following screenshot shows the AutoPrep point-and-click interface:
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This page contains the following information. Refer to Transforming Data with AutoPrep to learn more about using AutoPrep.
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Available for Ultra Pipelines
Limitations
You cannot modify the AutoPrep Snap Label.This Snap does not support have views or an error handling tab.
AutoPrep can flatten leaf nodes, but cannot flatten objects.
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The following table describes AutoPrep error messages:
Error | Reason | Resolution |
|---|---|---|
Looks like we couldn’t find a connector here. Please add a connector before you use the AutoPrep experience. | An upstream Snap must provide the sample data for AutoPrep. | Add a valid Snap that outputs JSON before the AutoPrep Snap. |
We couldn’t find any preview data. Please try running the validation again before we can get to AutoPrepping. | The upstream Snap is not valid. | Make sure the data source is connected and that the upstream Snap is outputting JSON. |
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