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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.
About datasets

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.
  - 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.

About datasets

A dataset specifies a collection of data to uploaded into the Precisely Data Integrity Suite Data Quality. This provides source data loaded into Data Integrity Suite and transformed by pipelines.

A dataset is presented in a tabular pattern. Each column corresponds to a field in the source data. Each row contains values for fields read in from source data, such as first name, last name, address, postal code, phone, membership date, and so forth. Fields in a dataset are characterized by field name, data type, and semantic type.

Data Settings can be configured to match the character encoding, field delimiter, text qualifier, and line separator in a particular data source. Data type formats for a dataset can be configured to recognize the numeric and date-time data types for data fields. These characterizations are used to suggest transformations in pipelines associated with a dataset.