How to get Azure SQL Database metadata in Microsoft Purview

We'll learn the techniques

Register Azure SQL Database data sources (SOURCES, REGISTER, MAP VIEW):In

• Purview, you can register data sources, such as Azure SQL Database, so that the service can discover, classify, and govern the data. This involves using tools to record and map the data sources, providing a visualization of the data topology.

Configure Key Vault connection (CREDENTIALS):

• To ensure the security of access credentials, Azure Purview allows you to configure the connection to Azure Key Vault. This involves creating credentials and configuring the connection to securely store and retrieve sensitive information.

(SECRETS):

• When using Azure Key Vault, you can configure database access credentials, storing them as secrets in Key Vault. This helps protect sensitive information and ensures that only authorized applications can access it.

(ACCESS POLICIES, KEY PERMISSIONS):In Key Vault

• access policies determine who has permissions to perform operations on keys, secrets, and certificates. Setting up proper access policies ensures that only authorized users have required permissions.

Scan Azure SQL Database (SCAN, SCOPE, RULE SET, TRIGGER):

• Database scanning in Azure Purview involves defining scopes, rule sets, and triggers to identify and classify sensitive data, providing a comprehensive view of data assets and potential compliance risks.

Search for existing objects in the data catalog (SEARCH, DATA CATALOG):

• Azure Purview has a data catalog search functionality, allowing users to find existing objects such as tables, columns, and datasets. This makes it easier to find and understand available data assets.

table metadata (SCHEMA, ASSET DESCRIPTION, CONTACTS):

• In the Azure Purview data catalog, you can identify and change metadata associated with tables. This includes information about the table schema, asset descriptions, and contact details. This metadata provides additional context and information about the data.

These steps are essential for efficient data management, ensuring security, compliance, and facilitating discovery and understanding of available data assets.