[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-02-01。"],[[["\u003cp\u003eData Catalog is a centralized inventory within Dataplex that automatically catalogs metadata from various Google Cloud sources, including BigQuery, Vertex AI, Pub/Sub, Spanner, and more, enabling organization-wide metadata search and discovery.\u003c/p\u003e\n"],["\u003cp\u003eData Catalog addresses challenges such as difficulty in finding, understanding, and utilizing data by providing a unified view, enriching data with metadata, improving data management, and fostering data ownership.\u003c/p\u003e\n"],["\u003cp\u003eData Catalog offers functionalities like searching for accessible data entries, tagging data entries with metadata, and providing column-level security for BigQuery tables, thus enhancing data discoverability and governance.\u003c/p\u003e\n"],["\u003cp\u003eData Catalog indexes both technical and business metadata, allowing for predicate-based searches, and while it catalogs metadata, it does not index the data within a data entry.\u003c/p\u003e\n"],["\u003cp\u003eData catalog can catalog metadata from non-Google Cloud systems using community-contributed connectors or manually building with the Data Catalog APIs.\u003c/p\u003e\n"]]],[],null,["# Data Catalog overview\n\nData Catalog is a central inventory\nof an organization's data assets. Data Catalog automatically\ncatalogs metadata from Google Cloud sources such as BigQuery,\nVertex AI, Pub/Sub, Spanner, Bigtable,\nand more. Data Catalog also indexes table and fileset metadata\nfrom Cloud Storage through [discovery](/dataplex/docs/discover-data).\n\nYou can discover data with Dataplex Universal Catalog's governed organization-wide\nmetadata search capability. You can further enrich metadata with critical\nbusiness context, and enable lineage tracking, data profiling, data quality\nchecks, and access control capabilities.\n\nUsing Data Catalog, organizations can achieve better data\ndiscovery, metadata management, and governance.\n\nWhy do you need Data Catalog?\n-----------------------------\n\nMost organizations deal with a large and growing number of data assets.\nData stakeholders (consumers, producers, and administrators) within an\norganization face multiple challenges, including the following:\n\n- **Searching for insightful data**:\n\n - Data consumers don't know the location and origin of data. They have to navigate data \"swamps\".\n - Data consumers don't know what data to use to get insights because most data isn't well documented and, even if documented, isn't well maintained.\n - Data can't be found and is often lost when it resides only in people's minds.\n- **Understanding data**:\n\n - Is the data fresh, clean, validated, approved for use in production?\n - Which dataset out of several duplicate sets is relevant and up-to-date?\n - How does one dataset relate to another?\n - Who is using the data and who is the owner?\n - Who and what processes are transforming the data?\n- **Making data useful**:\n\n - Data producers don't have an efficient way to put forward their data for\n consumers. If there's no self-service, consumers may overwhelm producers.\n Several data engineers can't manually provide data to thousands of data\n analysts.\n\n - Valuable time is lost if data consumers have to find out how to request\n data access, wait without a defined response time, escalate, and wait again.\n\nWithout the right tools, the challenges become a major obstacle\nto the efficient use of data. Data Catalog provides a centralized\nrepository that lets organizations achieve the following:\n\n- Gain a **unified view** to reduce the pain of searching for the right data.\n- Support data-driven decision making and accelerate the insight time by enriching data with **technical and business metadata**.\n- Improve **data management** to increase operational efficiency and productivity.\n- Take **ownership** over the data to improve trust and confidence in it.\n\nData Catalog functions\n----------------------\n\nData Catalog provides three main functions:\n\n- Searching for data entries for which you have access\n- Tagging data entries with metadata\n- Providing [column-level security](/bigquery/docs/column-level-security-intro) for BigQuery tables\n\nIn addition, Data Catalog can build on the results of a\n[Sensitive Data Protection](/sensitive-data-protection/docs) scan to identify sensitive\ndata directly within Data Catalog in the form of tag templates.\n\nHow Data Catalog works\n----------------------\n\nData Catalog can catalog asset metadata from different Google Cloud systems.\n\nYou can also use Data Catalog APIs to integrate with [custom data sources](/data-catalog/docs/how-to/custom-entries).\n\nAfter your data is cataloged, you can add your own metadata to these assets using tags.\n**Figure 1.** Data Catalog reads metadata from Google Cloud services and custom data sources.\n\nData Catalog metadata\n---------------------\n\nData Catalog handles two types of metadata: **technical metadata** and **business metadata** . To know more about metadata, see [Data Catalog metadata](/data-catalog/docs/concepts/metadata).\n\nSearch and discovery\n--------------------\n\nData Catalog offers a powerful predicate-based search\nexperience for technical and business metadata associated with a data entry. You\nmust have the permissions to read the metadata for a data entry so that you can\napply search and discovery on the metadata. Data Catalog does not\nindex the data within a data entry. Data Catalog only indexes the\nmetadata that describes an asset.\n\nData Catalog controls some metadata such as user-generated tags.\nFor all metadata sourced from the underlying storage system,\nData Catalog is a read-only service that reflects the metadata\nand permissions provided by the underlying storage system. You can make edits in\nthe underlying storage system to add, update, or delete the metadata of a data\nentry.\n\nTo know more about Data Catalog search, see\n[Search for data assets with Data Catalog](/data-catalog/docs/how-to/search).\n\n### Automatic cataloging of assets\n\nFor a given project, Data Catalog automatically catalogs the\nfollowing Google Cloud assets:\n\n- BigQuery sharing (formerly Analytics Hub) linked datasets\n- BigQuery datasets, tables, models, routines, and connections\n- Bigtable instances, clusters, and tables (including column family details)\n- Dataplex Universal Catalog lakes, zones, tables, and filesets\n- Dataproc Metastore services, databases, and tables\n- Pub/Sub topics\n- Spanner instances, databases, tables, and views\n- [Vertex AI models](/vertex-ai/docs/model-registry/introduction),\n [datasets](/vertex-ai/docs/datasets/overview), and\n [Vertex AI Feature Store resources](/vertex-ai/docs/featurestore/latest/overview)\n\n | **Note:** If a project name contains `:`, Dataplex Universal Catalog doesn't catalog `FeatureView` and `Feature` resources created in that project.\n\nIn addition to cataloging assets within the project IDs for which you have metadata access, Data Catalog can catalog data stored in the BigQuery projects\nthat contain public datasets.\n\n### Catalog non-Google Cloud assets\n\nTo catalog metadata from non-Google Cloud systems in your organization, you can use the\nfollowing:\n\n- [Community-contributed connectors](/data-catalog/docs/integrate-data-sources#integrate_on-premises_data_sources) to multiple popular on-premises data sources\n- Manually build on the [Data Catalog APIs for custom entries](/data-catalog/docs/integrate-data-sources#integrate_unsupported_data_sources)\n\nAccess Data Catalog\n-------------------\n\nYou can access Data Catalog functionalities using:\n\n- Dataplex Universal Catalog in the [Google Cloud console](https://console.cloud.google.com/dataplex)\n\n- [`gcloud`](/sdk/gcloud/reference/data-catalog) command-line interface (CLI)\n\n- [Data Catalog APIs](/data-catalog/docs/reference#data-catalog-api-reference)\n\n- [Cloud Client Libraries](/data-catalog/docs/reference/libraries)\n\nWhat's next\n-----------\n\n- Learn how to\n [tag a BigQuery table by using Data Catalog](/data-catalog/docs/quickstarts/quickstart-search-tag).\n\n- Learn how to\n [search data assets with Data Catalog](/data-catalog/docs/how-to/search).\n\n- Learn how to\n [integrate Google Cloud and on-premises data sources with Data Catalog](/data-catalog/docs/integrate-data-sources)."]]
