Study Notes — Certification Prep

Data Catalog
Study Guide

Fully managed and scalable data discovery and metadata management service. Empowers organizations to quickly discover, understand, and manage all their data in Google Cloud.

Updated: April 2026

Version: 1.0

Category: Metadata Management

Reading Time: ~15 min

Author: Michaël Bettan

Definition & Use Cases

What is Data Catalog?

Data Catalog is a fully managed and scalable data discovery and metadata management service that empowers organizations to quickly discover, understand, and manage all their data in Google Cloud.

SLA

99.9%

Use Cases

Data Discovery: Quickly find and understand data assets across your organization.
Data Governance: Enforce data policies and ensure data quality.
Data Catalog Management: Centralized management of metadata across different teams and projects.

Billing

Metadata storage: Business metadata as well as any on-premises metadata ingested. Measured in binary gigabytes (GiB).
Data Catalog API calls: Read, write, and search API calls.

Core Functionality & Concepts

Core Functionality

Scalability: Automatically scales to handle large volumes of metadata.
Auto-Cataloging: Automatically discovers and catalogs metadata from various services (BigQuery, Pub/Sub, Bigtable, Cloud Storage) during ingest operations. Supports manual and API-driven cataloging.
Metadata Types: Supports both technical (schema, location, etc.) and business metadata (tags, descriptions, ownership, etc.).
Search & Discovery: Provides a user-friendly search interface for quickly finding relevant data assets.
Security & Compliance: Integrates with IAM for granular access control and with Cloud DLP for data sensitivity detection and classification.

Key Concepts

Metadata Types:
- Technical metadata: Project information, asset name, schema name, description for BigQuery, etc. Always linked to a technical metadata entry.
- Business metadata: Tags, data stewards, rich text overview, PII, delete-by dates, business logic.
Attribute types: String, Boolean, Double, Enum.
Two main functions: Searching for data entries for which you have access, and Tagging data entries with metadata.
Structured Tags: Allows adding custom business metadata as key-value pairs to tables and columns within BigQuery. Example: {"department": "Sales", "data_owner": "John Doe", "sensitivity": "Confidential"}.

Tags & Tag Templates

Tags and Tag Templates

Tags: Enable organizations to create, search and manage metadata for all their data assets in a unified service. Tags are annotations or "business metadata".
Tags contain one or more fields where information can be stored.
The fields in a tag are defined by a tag template, and each field can be used to store one or more values.
Every tag is an instance of a tag template, which can be applied to an entire data asset, or to particular tables or columns.
Tag templates: Define a new (custom) template or reuse an existing public template.

Ingestion & Cataloging Methods

Data Ingestion & Cataloging

Automatic Ingestion: During data loading into supported services (BQ, Pub/Sub, Bigtable, GCS).
Manual Ingestion: Using the Data Catalog UI or the API.
Third-Party Tool Integration: Integrate with third-party tools and ETL processes to ingest metadata.

Entries & Entry Groups

Entries and Entry Groups

Entries: Represent data resources (GCP resources like BigQuery dataset or table, Pub/Sub topic, etc., or custom resources with custom data types).
Entries are contained in an entry group.
An entry group is a set of logically related entries together with IAM policies that specify the users who can create, edit, and view entries within an entry group.

Self-Assessment Questions

Q1. What are the two main types of metadata handled by Data Catalog?

Technical metadata (e.g., schema, location) and Business metadata (e.g., tags, descriptions).

Q2. What defines the fields in a tag in Data Catalog?

The fields in a tag are defined by a Tag Template.

Q3. How are entries organized for access control in Data Catalog?

Entries are contained in an Entry Group, which holds logically related entries and associated IAM policies.

Data CatalogStudy Guide