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Learn the basics of how to import, wrangle, execute jobs, profile, and export your data from Dataprep by Trifacta.


Dataprep by Trifacta enables analysts, data specialists, and other domain experts to quickly cleanse and transform datasets of varying sizes for use throughout the enterprise. Using an innovative set of web-based tools, you can import complex datasets and wrangle them for use in virtually any target system. Key capabilities include:

  • Import from flat file, databases, or distributed storage systems

  • Locate and remove or modify missing or mismatched data 
  • Unnest complex data structures
  • Identify statistical outliers in your data for review and management
  • Perform lookups from one dataset into another reference dataset
  • Aggregate columnar data using a variety of aggregation functions
  • Normalize column values for more consistent usage and statistical modeling
  • Merge datasets with joins
  • Append one dataset to another through union operations

Most of these operations can be executed with a few mouse clicks. This section provides a basic overview of common tasks through Dataprep by Trifacta.


Before you begin, please verify the following:

  • Dataprep by Trifacta account: You have a Dataprep by Trifacta account and can login. 

  • Example data: You should use a sample set of data during this task.

Basic Task

  1. Import data: Integrate data from a variety of sources of data.

    Tip: When you login for the first time, you can immediately upload a dataset to begin transforming it.

    Import Basics.

  2. Profile your data: Before, during, and after you transform your data, you can use the visual profiling tools to quickly analyze and make decisions about your data. See Profiling Basics.
  3. Build transform recipes: Use the various views in the Transformer Page to build your transform recipes and preview the results on sampled data. See Transform Basics.
  4. Sample your data: In  Dataprep by Trifacta, you create your recipes while working with a sample of your overall dataset. As needed, you can take new samples, which can provide new perspectives and enhance performance in complex flows. See Sampling Basics.

  5. Run job: Launch a job to run your recipe on the full dataset. Review results and iterate as needed. See Running Job Basics.

  6. Export results: Export the generated results data for use outside of Dataprep by Trifacta. See Export Basics.

Object overview: You should review the overview of the objects that are created and maintained in  Dataprep by Trifacta. See Application Asset Overview.

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