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Data Quality
Assure reliability, consistency, and accuracy data from different sources to deliver value to employees and customers.
Data Quality pipelines
Pipelines define and apply transforms to data loaded by a dataset.
How to
Edit a pipeline
Edit a pipeline to view, add, or edit transforms that it applies to uploaded data.

Welcome
The Precisely Data Integrity Suite is designed to deliver trusted data with accuracy, consistency, and context – built on the core capabilities of data integration, data quality, data governance, location intelligence, and data enrichment.
Data Integration
Replicate data from mainframe, IBM i, and relational databases to cloud analytics platforms.
Data Observability
Proactively monitor and manage the health of your data. Receive actionable insights through alerts that drive business decisions.
Data Governance
Manage data policy and processes with greater insight into your data's meaning, lineage, and impact.
Data Quality
Assure reliability, consistency, and accuracy data from different sources to deliver value to employees and customers.
- Data Quality Catalogs
  The Data Integrity Suite Data Catalog lets users discover and understand connected data sources.
- Data Quality datasets
  A dataset defines a data source and characterizes data to be loaded and transformed by pipelines.
- Data Quality pipelines
  Pipelines define and apply transforms to data loaded by a dataset.
  - About Data Quality pipelines
  - Using Data Quality pipelines
  - How to
    - Create a pipeline on the Pipelines page
      Create a pipeline to import and transform data from a dataset.
    - Edit a pipeline
      Edit a pipeline to view, add, or edit transforms that it applies to uploaded data.
    - Add steps to a pipeline
      Transforms are configured to form transformation steps in a pipeline. These steps change the format, structure, or values of data uploaded by a dataset. A pipeline may perform any number of transforms in the order determined by the order of the transformation steps.
    - Edit a step in a pipeline
      Edit a transform settings for a step in a pipeline to change its behavior. You may also reorder or delete transformation steps in a pipeline.
    - Preview a transformation step in pipeline
      You can quickly preview the outcome of any step in a transformation without opening the transformation operator settings.
    - Rename a step in pipeline
      This procedure describes how to quickly rename a step in a pipeline without editing the step.
    - Filter rows that match data in a pipeline
      While editing a pipeline, you can filter out rows in the inspection table that do not contain specified data.
    - Rename a pipeline
      You can rename a pipeline on the Pipelines page.
    - Duplicate a pipeline
      You can duplicate an existing pipeline to use it for a new pipeline. A duplicate pipeline initially consists of the same dataset and transformation steps as the original pipeline. Configurations are not copied.
    - Delete a pipeline
      You can delete a pipeline from the Pipelines page.
    - Select columns in a pipeline step
      There are several methods using the mouse or keyboard to select columns for a pipeline step. When you edit settings for a transform step, use any of these methods to add columns to the Columns box.
    - Delete a transform step from a pipeline
      Use the Delete command on the transform step shortcut menu to delete a transform step from a pipeline.
  - Reference
    This section contains reference information for pipeline pages in Precisely DQ.
- Data Quality jobs
- Data Connections
  Connecting to data is the first step in processing, analyzing, and storing information.
Administration
Manage your subscription, your users and their roles, and other system tasks.

Edit a pipeline

Edit a pipeline to view, add, or edit transforms that it applies to uploaded data.

On the Precisely Quality page, expand the secondary navigation menu, and click Pipelines .
In the Name column, find the pipeline that you want to edit.
In the Search box , you can match all or part of a pipeline title to filter pipelines shown in the table.

Tip: In the Dataset column, you can first scroll down to first find the dataset for a pipeline.
In the Name column, click the context menu button , then click Edit.

Completing this procedure opens the pipeline page. On this page you can view sample data as you add transformation steps to the pipeline. The pipeline page consists of three panes. The upper pane shows transformation steps in the pipeline. The table under that shows the state of the data before or after a transformation step. A third pane expands from the side when you add or edit a transformation step. It exposes options that you can edit for a selected transform.

You can now view sample data from the associated dataset and add transformation steps to the pipeline.