Azure Data Studio is an open-source data management tool that enables working with SQL Server, Azure SQL DB, and Azure Synapse from Windows, macOS, and Linux. It is a one-stop shop to query, design, and manage your databases and data warehouses, on-premise or in the cloud. In this article, we will see 5 most interesting features of Azure Data Studio for SQL developers.
Databricks platform is used to connect to multiple applications. Databricks requires credentials or secrets to connect to these applications. Databricks or Azure Key Vault can store these secrets securely. Secret scopes are used to manage the secrets which are stored in Azure Key Vault or Databricks.
Mounting object storage to Databricks fie system allows easy access to object storage as if they were on the local file system. In this article, we will see how to mount and unmount data lake in Databricks.
In this article, we will see how to call a notebook from another notebook in Databricks and how to manage the execution context of a notebook.
Azure Data Factory uses Integration Runtimes as a compute infrastructure to execute data movement and data transformation activities. This article describes how to set up Azure Data Factory Shared Integration Runtime.
To secure connection details in data factory, we can store credentials in the Azure key vault and access them in Azure data factory. This article describes how to access Azure key vault secrets from Azure data factory linked services.
This article describes how to get local time zone date in Azure SQL database using an user defined scaler function and AT TiME ZONE.
Microsoft has enabled support for accessing Microsoft Graph API from Azure data factory. In this article, we will see how to call Graph API from Azure data factory using the managed identity.
Migrate Azure data factory from one resource group to another using these 3 simple steps.
This article describes how to create and configure a self-hosted Azure DevOps agent in an on-premise Windows machine.
