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Trifacta Dataprep



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If you licensed Dataprep by Trifacta before Oct. 14, 2020, you are using the Dataprep by Trifacta Legacy product edition. On October 14, 2022, this product edition will be decommissioned by Google and will be no longer available for use. Current customers of this product edition are encouraged to transition to one of the product editions hosted by Trifacta. See Product Editions.

   

Dataprep by Trifacta® can import data from a variety of flat file formats and other distributed sources.

NOTE: Dataprep by Trifacta does not modify a source. Instead, a set of metadata is associated with the source data, which enables transformation of the source. On export, a new version of the data is written to one or more specified output destinations.

Steps:

When data is imported, a reference to it is stored by the platform as an imported dataset. The source data is not modified. In the application, you modify the recipe associated with a dataset to transform a sample of the imported data.

NOTE: Any user with a valid user account can import data from a local file.

  1. Login to the application.

  2. In the menubar, click Library. Click Import Data.
  3. To add a dataset:

    1. Select the connection where your source is located. 
    2. Upload: 
      1. Select Upload to upload a file from your local desktop. You can select multiple files to upload. For this example, select only one file.
      2. Navigate and select the file or files for your source. Click Open.
    3. Backend storage, such as S3:
      1. Navigate and select the file or files for your source.
      2. To queue the dataset for uploading, click the Plus icon next to its name.
      3. You can select multiple files.
    4. Select the Add to new flow checkbox. This option creates a new flow, which is a container object for your Trifacta assets. Your imported dataset is added to it.
  4. To begin working with your dataset, click Continue

  5. The imported dataset and its containing flow are created. 
  6. You can begin working with the dataset in the Transformer page. For more information, see Transform Basics.

Tip: If you are interested, you can create a visual profile of your source data before you begin transforming. For more information, see Profiling Basics.

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