Environment Setup for Designing ADF Data Pipelines

Data pipelines are a key aspect of modern data integration processes, allowing businesses to automate the movement of data from various sources to their intended destinations. ADF allows for the creation of complex data pipelines both using Azure CLI and the ADF Studio in Azure portal UI. In this lesson, we’ll cover the basics of data pipelines, how they work in ADF, and prepare our Azure environment for creating an ADF data pipeline.

What is a data pipeline?

A data pipeline is a sequence of data processing steps that are orchestrated to transform data from a source to a target system. The pipeline consists of interconnected stages, which represent individual processing steps. These stages are usually designed to extract, transform, and load (ETL) data. However, the scope of a data pipeline can vary depending on the use case and may include other data processing operations such as data ingestion, data processing, and data synchronization.

Data pipelines in ADF

ADF provides a flexible and scalable platform for designing data pipelines. With its wide range of supported connectors and built-in transformations, ADF enables developers to easily create pipelines that can move and transform data between various data sources and destinations. These sources and destinations can include on-premises and cloud-based systems, such as relational databases, data warehouses, and big data stores.

Azure-readableThe illustration above explains a basic data pipeline completing a copy activity in ADF. A linked service is first used to connect the source data storage with ADF, and then convert the source data into an Azure readable format. The copy data activity inside ADF then transforms the data into a table dataset that Azure storage will read, and another linked service sends the copied and formatted data into the destination storage account. In the next few sections, we’ll perform this copy activity.

Designing data pipelines using Azure CLI

Azure’s CLI support can be used to set up, design, run, and maintain data pipelines. In this lesson, we will prepare the prerequisites for designing a pipeline.

This lesson will focus on creating all resources required for building a data pipeline into a new resource group. This is ...