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Data Quality
Assure reliability, consistency, and accuracy data from different sources to deliver value to employees and customers.
Data Quality datasets
A dataset defines a data source and characterizes data to be loaded and transformed by pipelines.
How to
This section contains tasks for using datasets in Precisely DQ.

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.
  - About datasets
  - Using datasets
    Datasets are created, edited, and deleted on the Datasets page of the Data Quality application. You can also create a pipeline that uses a selected dataset on this page.
  - How to
    This section contains tasks for using datasets in Precisely DQ.
    - Create a dataset
      This procedure describes how to upload and create a dataset from a text file.
    - Edit a dataset
      After you create a dataset, edit settings to match file content. You can also edit field names, data types, and semantic types that identify and characterize data.
    - Delete a dataset
      You delete a dataset from the Datasets page.
    - Edit data type formats for a dataset
      Perform this procedure to determine how data types are characterized for date, time, and numeric fields in a dataset.
    - Create a pipeline from a dataset
      Create a Data Quality pipeline to import and transform data from a dataset.
  - Reference
    This section contains reference information for dataset pages in Precisely Data Quality.
- Data Quality pipelines
  Pipelines define and apply transforms to data loaded by a dataset.
- 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.

How to

This section contains tasks for using datasets in Precisely DQ.

Task	Description
Create a dataset	Create a Data Quality dataset
Edit a dataset	Edit a Data Quality dataset
Delete a dataset	Delete a Data Quality dataset
Edit data type formats for a dataset	Edit data type formats for a Data Quality dataset
Create a pipeline from a dataset	Create a Data Quality pipeline to import and transform data from a dataset.