Trifacta® Wrangler Enterprise 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 Enterprise.
Before you begin, please verify the following:
Trifacta account: You have a Trifacta account and can login.
- If you are importing data from a location other than your local file system, you must have the appropriate role in your user account. See Import Basics.
- Example data: You should use a sample set of data during this workflow.
- Review object overview: Before you begin, you should review the overview of the objects that are created and maintained in Trifacta Wrangler Enterprise. See Object Overview.
- Import data: Integrate data from a variety of sources of data. See Import Basics.
- 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.
- 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.
Sample your data: In Trifacta Wrangler Enterprise, 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.
Run job: Launch a job to run your recipe on the full dataset. Review results and iterate as needed. See Running Job Basics.
- Export results: Export the generated results data for use outside of Trifacta Wrangler Enterprise. See Export Basics.
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