Category : Microsoft Azure Data Engineering | Sub Category : Practice Assessment for Exam DP-203 - Data Engineering on Microsoft Azure | By Prasad Bonam Last updated: 2023-09-10 03:20:47 Viewed : 1016
Which Azure Data Factory components should you use to connect to a data source?
Ans: a linked service
Linked services allow you to connect to your data source.
Datasets are the databases that are available via the linked service.
Activities contain the transformations or analysis of data factories.
Pipelines are groups of activities.
Understand Azure Data Factory components - Training | Microsoft Learn
In Azure Data Factory, you typically use the following components to connect to a data source:
Linked Services: Linked Services are used to define the connection information to your data source or destination. They store the connection string, authentication details, and other configuration information required to connect to various data platforms such as databases, storage accounts, and more. Azure Data Factory supports a wide range of linked services for different data sources, including Azure SQL Database, Azure Blob Storage, on-premises SQL Server, and more.
Datasets: Datasets represent the structure or schema of the data you want to work with in Azure Data Factory. Datasets define the data format, location (linked service), and additional settings like file format or table name. Datasets can be thought of as pointers to your data, whether it is in a file, table, or other data source.
Data Flows: Data Flows are used to define data transformation logic. While they are not used directly for connecting to data sources, they are crucial for transforming and moving data between datasets. You design data flows to perform actions like data wrangling, transformation, aggregation, and mapping between source and destination datasets.
Activities: Activities are the building blocks of Azure Data Factory pipelines. They represent individual actions or operations that need to be performed within a pipeline. Activities can include data movement activities (e.g., copy data from source to destination), data transformation activities (e.g., data flows), and control flow activities (e.g., branching and conditional execution).
To connect to a data source, you typically start by creating a Linked Service that defines the connection details to that source. Then, you create a dataset that references the Linked Service and defines the structure of the data you want to work with. Finally, you use activities within your pipeline to perform various operations, including reading from or writing to the data source using the defined datasets and linked services.
These components work together to enable data integration, data movement, and data transformation within Azure Data Factory pipelines.