Dataplex Catalog Overview | Google Cloud

This document describes the Dataplex catalog, which provides a platform for storing, managing, and accessing metadata.

The Dataplex catalog provides a unified inventory of Google Cloud resources, such as BigQuery, and other resources, including on-premise resources. Metadata for Google Cloud resources is automatically collected, and metadata for third-party resources can be ingested into the Dataplex catalog.

Dataplex Catalog allows you to enrich your inventory with additional business and technical metadata to capture context and knowledge about your resources. Dataplex Catalog enables data search and discovery across your organization and enables data governance over your data assets.

Note: This document describes the features of the Dataplex Catalog. For more information about the Data Catalog, see Data Catalog Overview. Use Cases

Using the Dataplex catalog, you can:

Discover and understand your data: The Dataplex catalog provides visibility into data resources across your organization, allowing you to find resources relevant to your data consumption needs. It provides context for data resources, helping you understand their suitability for your data consumer needs.

Enable Data Governance and Data Management: Dataplex Catalog provides metadata that can inform and enhance data governance and data management capabilities.

Maintain a scalable, comprehensive repository for metadata. The Dataplex catalog stores and provides access to metadata automatically collected from Google Cloud resources. You can integrate your own metadata from non-Google Cloud systems. You can enrich all metadata with additional business and technical metadata annotations.

How the Dataplex catalog works

The Dataplex catalog is based on the following concepts:

Entry: An entry represents a data asset. Most of the metadata is described by aspects within the entry. This is similar to an entry in a data catalog. For more information, see Entry.

Aspects: An aspect is a set of related metadata fields within an entry. An aspect can be interpreted as a component of an entry or as additional metadata to an entry. It is similar to tags in a data catalog, but aspects are stored within an entry rather than as a standalone resource. For more information, see Aspects.

Aspect Types: An aspect type is a reusable template for an aspect. Every aspect is an instance of an aspect type. This is similar to a tag template in Data Catalog. For more information, see Aspect Types.

Entry Group: An entry group is a container for entries that acts as a unit of management for entries. For example, use an entry group to configure IAM access control, project attributes, or location for the entries in the entry group. This is similar to entry groups in Data Catalog. For more information, see Entry Groups.

Entry Type: An entry type is a template for creating entries. An entry type establishes key metadata elements outlined as a list of required aspects for entries of this type. For more information, see Entry Types.

Figure 1. Entries and Entry Groups Figure 2. Aspect Types and Entry Types

Below are some examples of how the Dataplex Catalog can be used:

Data analysts or business analysts can search for entries across the organization and explore the metadata associated with the entries. For more information, see Searching Data Assets. Data owners or data governors can annotate entries with aspects to capture additional technical and business metadata. For more information, see Managing Aspects and Enriching Metadata. Data owners or data governors can enforce consistency in metadata by defining annotation standards (using aspect types) and custom entries (using entry types). For more information, see Managing Aspects and Enriching Metadata. Data engineers can have a unified inventory of resources, including Google Cloud resources and resources from third-party systems. Google Cloud resources are collected automatically by Dataplex Catalog and non-Google Cloud resources are collected by the user. For more information, see Managing Entries and Ingesting Custom Sources.

If you're already using Data Catalog, note the following:

Custom entries, summary contexts, and entry groups created in Data Catalog are available in Dataplex Catalog. Tags and tag templates created in Data Catalog are not available in Dataplex Catalog. Searching for data assets in Dataplex Catalog includes both metadata created directly in Dataplex Catalog and metadata ingested into Dataplex Catalog from Data Catalog. Searching for data assets in Data Catalog includes only metadata created in Data Catalog. If the description of an entry group in Data Catalog is longer than 1024 characters, it is truncated to 1024 characters in Dataplex Catalog. Dataplex Catalog vs Data Catalog

The Dataplex Catalog provides the ability to manage metadata in Dataplex, with independent metadata storage and a new set of API methods integrated into the Dataplex API.

Key features of Dataplex Catalog include:

A more robust metamodel

Typed Entries. Allows enforcement of minimum metadata standards by defining required metadata content for custom entries. A user-configurable metamodel for custom entries makes custom ingestion more robust and custom metadata more consistent and comprehensive. Supports more diverse and complex metadata, including support for nested structures such as lists, maps, and arrays.

Scalability improvements include the ability to interact with all metadata associated with an entry through a single atomic CRUD operation, and the ability to retrieve multiple metadata annotations associated with a search or list response.

The following table compares the features of Dataplex Catalog and Data Catalog.

Comparison of Dataplex Catalog and Data Catalog Features Dataplex Catalog Data Catalog Supported Google Cloud Sources All sources described in the Supported Google Cloud Sources section of this document. All sources described in Entries and Entry Groups. Ingesting Custom Sources

Populating custom entries with a managed structure defined by the entry type.

Data catalog custom entries and entry groups are made available in the Dataplex catalog with generic entry types.

Ingestion into generic custom entries. Enrich Metadata The metadata context of an entry is captured using aspects and aspect types. The metadata context of an entry is captured using tags and tag templates. Search Searches are performed across: All Google Cloud sources listed in Supported Google Cloud Sources, custom entries created in the Dataplex catalog, aspects created in the Dataplex catalog, custom entries created in Data Catalog and ingested into the Dataplex catalog

Search results include only resources that belong to the same VPC-SC boundary as the project the search is performed in. If you use the Google Cloud console, this is the project selected in the console.

The search is performed across: all Google Cloud sources described in Entries and Entry Groups, custom entries created in Data Catalog, and tags created in Data Catalog.

The following table shows how Dataplex catalog resources correspond to Data Catalog resources.

Mapping Between Dataplex Catalog and Data Catalog Resources Dataplex Catalog Resources Data Catalog Resource Description Aspect Type (Global) Public Tag Templates Tag templates are regional resources. However, you can use them to create tags across regions. Tag templates correspond to global aspect types in the Dataplex catalog. Optional Aspects Public Tags Public tags in Data Catalog correspond to optional aspects in the Dataplex catalog. Entry Groups Entry Groups For Google Cloud sources, the Dataplex catalog establishes system entry groups, such as @bigquery, for each project. Custom Entries Required Aspects Custom Entries

The Data Catalog and Dataplex Catalog share a similar concept regarding custom entries.

Standard entry properties are modeled as required aspects of the Dataplex catalog.

Required aspects of system entries System (Google Cloud) Entry Metadata that describes built-in entities, such as the schema of a BigQuery table, is captured in required aspects of the system-defined aspect type.

For more information about features available in the Data Catalog that are not supported in the Dataplex Catalog, see the Features Not Supported in Dataplex Catalog section of this document.

Supported Google Cloud Sources

Metadata from the following Google Cloud sources is automatically ingested into the Dataplex catalog:

Analytics Hub exchange and listings BigQuery datasets, tables, models, routines, connections, linked datasets Bigtable instances, clusters, tables (including column family details) Cloud SQL instances, databases, schemas, tables, views Dataproc Metastore services, databases, tables Pub/Sub topics Spanner instances, databases, tables, views Vertex AI models, datasets Project and location constraints

Dataplex catalog resources are stored in various projects and locations. The following restrictions apply:

position:

The entry location must match the entry type location or the entry type must be global. The aspects added to the entry must be based on aspect types stored in the same location as the entry or the aspect type must be global. The entry type must consist of aspect types stored in the same location as the entry type.

project:

If an entry type references a custom aspect type, the aspect type must exist in the same location and project as the entry type. Features not supported in the Dataplex catalog

The following features available in the Data Catalog are not supported in the Dataplex Catalog:

The concept of private aspects and aspect types is not supported in Dataplex Catalog. Access to aspects is controlled by the permissions associated with the entry that contains the aspect. For more information, see Dataplex IAM Roles. Searching for policy tags is not supported in Dataplex Catalog search. Therefore, the predicates policytag and policytagid do not work in Dataplex Catalog search. For Data Catalog custom entries ingested into Dataplex Catalog, existing IAM permissions in the current metadata are not automatically propagated to the copied metadata. You must explicitly configure IAM permissions before using the copied metadata. Submitting the results of sensitive data protection jobs to Dataplex Catalog is not supported. You cannot list entry types and aspect types across projects using the API. You can only scope a list request to the project. You cannot attach business glossary terms to columns in Dataplex entries. You cannot change the list of required aspect types in an entry type after you create it. Pricing

Dataplex charges for metadata storage using metadata storage SKUs, see Dataplex Pricing for more information.

There is no charge for the following uses:

Creating and managing Dataplex catalog resources Dataplex catalog search API calls Search queries performed on the Dataplex catalog page in the Google Cloud console Next steps

Sources 1/ https://Google.com/ 2/ https://cloud.google.com/dataplex/docs/catalog-overview The mention sources can contact us to remove/changing this article

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