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This documentation applies to Trifacta Wrangler. Download this free product.
Registered users of this product or Trifacta Wrangler Enterprise should login to Product Docs through the application.

Trifacta® Wrangler enables analysts, data specialists, and other domain experts to quickly cleanse and transform datasets of varying sizes for use in other analytics systems. 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 

  • 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 workflows through Trifacta Wrangler.

Pre-requisites

Before you begin, please verify the following:

  1. : You have a  and can login. 
    1. If you do not have an account, you may be able to self-register through the application. 
  2. Example data: You should use a sample set of data during this workflow.

Basic Workflow

  1. Review object overview: Before you begin, you should review the overview of the objects that are created and maintained in Trifacta Wrangler. See Object Overview.
  2. Import data: Integrate data from a variety of sources of data. See Import Basics.
  3. 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.
  4. 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.
  5. Generate Results: Launch a task to run your recipe on the full dataset. Review results and iterate as needed. See Generating Results Basics.

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

 

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