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NOTE:  Trifacta Wrangler is a free product with limitations on its features. Some features in the documentation do not apply to this product edition. See Product Limitations.

   

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

Overview

Trifacta® Wrangler 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 workflows through Trifacta Wrangler.

Prerequisites

Before you begin, please verify the following:

  • : You have a  and can login. 

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

Basic Workflow

  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.


    See 
    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  Trifacta Wrangler, 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 Trifacta Wrangler. See Export Basics.

Object overview: You should review the overview of the objects that are created and maintained in  Trifacta Wrangler. See Object Overview.

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