It is a cloud-based ETL (Extract, Transform, Load) service designed for serverless data integration and transformation at scale.

Key Features:

• Serverless Data Integration: Automates and orchestrates data workflows across various data sources.

• Scalability: Processes large-scale data with a scalable and cost-efficient model.

• Hybrid Data Movement: Supports both on-premises and cloud data sources.

• Data Transformation: Enables data ingestion, transformation, and processing.

Components

Datasets:

CSV Dataset: Refers to the Blob Storage linked service and defines the schema of the CSV file (columns, data types, etc.).

SQL Table Dataset: Refers to the SQL Database linked service and defines the schema of the target SQL table.

Activities:

It is defining a dataset involves specifying the schema and location of the data you want to interact with.

Ex: Source Dataset: Define a dataset pointing to an on-premises SQL Server.

Sink Dataset: Define a dataset pointing to an Azure SQL Database.

Copy Activity: Configure the Copy Activity to read from the source dataset and write to the sink dataset with necessary column mappings.

Execution: Run the pipeline to start the data copy process.

Data Flow:

• It provides a way to transform data at scale without any coding required.

• Data transformation jobs can be designed in the data flow designer by constructing a series of transformations.

Flowlet:

A reusable component in data flows that simplifies complex transformations

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