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Tuesday, January 17, 2023

What language is used in Azure Data factory?

 What language is used in Azure Data factory?

Azure Data Factory is Microsoft’s cloud-based data integration service that helps organizations move and transform data between disparate cloud and on-premises data stores. It is designed to help customers construct data pipelines to ingest, prepare, transform, analyze, and publish data. Azure Data Factory uses a number of languages and technologies to enable users to create data pipelines. These include the following:

  • 1. Azure Resource Manager (ARM) Template – ARM Templates are used to define the data pipelines in Azure Data Factory. ARM Templates are written in JSON, and allow you to define the resources, parameters, and outputs for your data pipeline.

  • 2. PowerShell – PowerShell is used to deploy and manage ARM templates, as well as to manage other Azure resources such as Azure Data Lake Storage.

  • 3. Azure Data Factory SDK – The Azure Data Factory SDK is used to programmatically interact with Azure Data Factory. It includes an object model, operations, and programming language bindings.

  • 4. .NET – .NET is used to write custom activities for Azure Data Factory. These activities are written in C# and can be used to perform custom tasks such as data transformation, image processing, and machine learning.

  • 5. Python – Python is used to write custom activities for Azure Data Factory. These activities are written in Python and can be used to perform custom tasks such as data transformation, image processing, and machine learning.

  • 6. Azure Data Lake Analytics – Azure Data Lake Analytics is a distributed query engine used to query data stored in Azure Data Lake Storage. It is used to run U-SQL scripts, which are written in a combination of C# and SQL.

  • 7. Azure Stream Analytics – Azure Stream Analytics is a real-time analytics service used to process data streams. Stream Analytics jobs are written in an SQL-like language that is optimized for stream processing.

Azure Data Factory also supports a number of other languages and technologies, such as Java, T-SQL, and JavaScript, which can be used to build custom activities and processes. With the combination of these languages and technologies, Azure Data Factory enables customers to construct powerful data pipelines that can ingest, prepare, transform, analyze, and publish data.