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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.

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
  - 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.

Data Quality pipelines

Pipelines define and apply transforms to data loaded by a dataset.

Organizations often gather data from multiple sources in multiple formats. When data is loaded into Data Integrity Suite, destination data stores may require different formats to be used in new ways. The format is often different while purposes require higher quality and consistency. A quality pipeline defines a series of steps to transform or clean data before a job loads it into its final destination. Data Quality pipelines can assure accuracy, consistency, uniqueness, integrity, and validity.