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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

  • 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 the Trifacta Application.

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 Trifacta 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 the Trifacta Application. 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.

If you walked through this workflow in the Trifacta Application, you have imported, cleansed, transformed, and possibly enhanced your data for use in the next step of your analytics pipeline. Hopefully, this process has given you insight into the easy-to-use tools at your disposal through the Trifacta Application and how quickly they can be brought to use in turning imported datasets into clean and actionable data for use across the enterprise.

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