The Precisely Data Catalog is a service for data-driven decision-making. It is a centralized repository of data assets and metadata that can be reused across different modules in Data Integrity Suite for replication, cleansing, enrichment, and observation. It helps you organize and manage your data assets in easy-to-understand formats that are accessible to all users. A business-ready catalog enables users to search for data, trace its origins, and understand its journey through the data supply chain without the complexity of technical terminology.
Catalog configuration guide
- Access catalog: Log in to Data Integrity Suite and go to the Data Catalog service.
- Connect datasources: Use the provided connectors to link your various data sources. Ensure all relevant datasources are connected for metadata collection.
- Configure metadata collection: Set up automated metadata collection. Define the frequency and scope of metadata collection according to your needs.
- Integrate technical metadata: Add technical metadata to ensure data accuracy and consistency.
- Define catalog rules: Establish and enforce rules to standardize metadata practices.
- Manage and monitor catalog jobs: Consistently manage and monitor catalog jobs and address any issues or errors promptly.
- Understand asset scores: View and evaluate asset scores to support informed decision-making.
- Sort and filter assets: Utilize sorting and filtering tools to improve the discoverability of your data assets.
- Organize data elements: Effectively organize datasources, datasets, and fields within the catalog.
Catalog assets overview
To view all your cataloged assets, go to Catalog. By default, the page displays information in card and list views, sorted alphabetically by asset name. For detailed insights into specific assets in the Data Integrity Suite, you can drill down further within each page:
- All Assets: A unified view of all cataloged assets across datasources, datasets, fields, technical assets, and business assets. Use this view to browse, search, and compare assets in one place.
- Datasources: Items representing external or internal data sources. View connections with details such as datasource name, number of datasets, and fields present.
- Datasets: Logical groupings of data extracted from sources.
View dataset name, location, associated datasource, and number of
fields. Hover over the Location name to see the
asset path in the format
Datasource>Schema>Dataset. You can also upload or generate sample data for a dataset to create a Data Quality pipeline. - Fields: Individual data attributes within datasets. View
field name, associated datasource name, and field type. Hover over the
Dataset name to see the asset path in the
format
Datasource>Schema>Dataset>Field. - Technical: View technical asset types, descriptions, and asset counts for each type. Depending on your assigned permissions, you can create, edit, or delete technical assets. Some Data Integrity Suite system-managed asset types are used for internal configuration and are not displayed in the Technical view.
- Business : Business-context assets such as business terms, metrics, and glossary items that define how data is understood and used. These assets help connect technical data to shared business meaning.
- Tags: Labels assigned to assets to classify and organize them by domain, project, status, or other categories. Use tags to quickly filter results and find related assets.
- Jobs: View jobs history to see the status and details of the cataloging process, and troubleshoot any issues that occur.
Access and visibility of catalog assets
Catalog displays only the assets and actions that you are authorized to access.
- With View permission, you can browse, search, and view catalog assets.
- With Create permission, you can create supported asset types.
- With Update permission, you can modify existing assets.
- With Delete permission, you can remove authorized assets.
- Unauthorized operations are blocked in the Catalog user interface and API requests.
- Permission checks apply regardless of how you reach a Catalog page. Direct URL navigation does not bypass Catalog security controls.
- Certain system-managed configuration asset types are used internally by Data Integrity Suite and are not displayed in Catalog asset views.
Example: A SalesDB datasource monitors sales transactions and comprises three datasets featuring fields such as SaleID, ProductID, Quantity, and SaleDate. Among these, the SalesRecords dataset, which contains four fields, is essential for organizing pertinent information for validation and reporting. Each dataset includes the SaleID field, which acts as a unique identifier for every sale, crucial for preventing duplication and ensuring accurate data relationships. Additionally, business assets such as the Sales Report offer an overview of operations, while technical assets such as the Data Warehouse function as a central repository for integrated data. Users can implement rules such as the Sales Amount Check to ensure that sales amounts are not negative, and manage tasks through jobs such as Job ID 002, which is currently in progress for data validation within the SalesDB datasource. Collectively, these elements work together to uphold data integrity and facilitate informed decision-making.
Required permissions for Catalog features
The actions available in Catalog depend on the permissions assigned to your user account.
Catalog applies permissions consistently across the interface and API operations.
| Permission | Actions |
|---|---|
| View | View catalog assets, metadata, scores, and jobs. |
| Create | Create catalog assets and supported configuration objects. |
| Update | Edit existing catalog assets and supported configuration objects. |
| Delete | Delete catalog assets and supported configuration objects. |
| Profile View | View profiling information associated with datasets and fields. |
| Metrics View | View quality and governance scores and related metrics. |
Metadata management
Metadata management in Data Integrity Suite involves the systematic handling of metadata to ensure data quality, compliance, and efficient data usage. It encompasses the collection, management, and discovery of metadata across various enterprise systems.
Catalog captures metadata from connected datasources, including hosts, connections, schemas, and datasets; so you can discover, browse, and understand your data assets. Catalog automatically collects metadata from datasources, and users curate it for reuse.
Data Integrity Suite includes three core metadata management features:
- Data Catalog: An inventory of enterprise data assets that helps you discover available data, see relationships between assets, and understand their quality.
- Business glossary: Stores definitions of business terms, KPIs, business dimensions, and other metadata linked to specific data assets.
- Data Lineage: Shows how data flows through your ecosystem, including source systems, destination systems, and derived data assets.
You can also catalog database views metadata. When you catalog a connection, you'll see database schema tables and views, and can harvest metadata from both to understand lineage between them.
By integrating metadata across data replication, data quality, and data observability scenarios, Data Integrity Suite simplifies metadata collection and enables automated data mapping, performance monitoring, and lineage tracking.
Catalog spatial data
Catalog spatial data before performing spatial analytics, such as using spatial operations in Data Integrity Suite pipelines. For example, you may have a spatial table representing store catchment areas boundaries, which you can utilize in a pipeline to assign a store ID to each customer record. Data Integrity Suite catalog process supports cataloging of spatial data tables in Snowflake. Both Snowflake spatial data types are supported:
- GEOGRAPHY data type, modeling Earth as a perfect sphere with coordinates in latitude and longitude using the WGS84 spatial reference system (EPSG:4326).
- GEOMETRY data type with coordinates projected to a flat surface as x and y coordinates pairs, often in meters. This data type can support any spatial reference systems defined by the EPSG (European Petroleum Survey Group). For more information, see https://epsg.org/home.html.