- Azure Data Factory is a cloud-based data integration service that allows you to create, schedule, and orchestrate data pipelines to move data from various sources to various destinations.
- It simplifies the process of data ingestion, transformation, and loading into Azure data storage services such as Azure Data Lake Storage, Azure SQL Database, and Azure Cosmos DB.
- In simple words, it is a tool for managing and automating data workflows in the cloud.
- It is the cloud-based ETL and data integration service that allows you to create data-driven workflows for orchestrating data movement and transforming data at scale.
- Data Factory contains a series of interconnected systems that provide a complete end-to-end platform for data engineers. Such as
– Ingest
– control flow
– Data flow
– Schedule
– Monitor
Some Examples to Understand azure Data Factory
- Let’s say you have a database containing customer information that is stored on-premises and you want to load this data into Azure SQL Database for further analysis.
- With Azure Data Factory, you can easily automate this process of moving data from the on-premises database to Azure SQL Database. You can create a data pipeline in Data Factory that specifies the source and destination of your data and any transformations you want to apply along the way. For example, you may want to clean the data, remove duplicates, or aggregate the data before loading it into Azure SQL Database.
- Once you have created the data pipeline, you can schedule it to run on a daily, weekly, or monthly basis, or you can trigger it manually. Data Factory will automatically move the data from the source to the destination, apply any transformations, and load the data into Azure SQL Database.
- In simple words, Azure Data Factory is a tool that helps you automate the process of moving and transforming data from one place to another, making it easier for you to get your data into the right place for analysis and insights.
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