Getting started with Azure data factory

Azure Data Factory, a cloud data integration service using that we can

1.  Create ETL/ELT data-driven workflows to process raw unorganised data from various data stores for data analysis

2.  Transform the data by using compute services such as Azure HDInsight Hadoop, Spark, Azure Data Lake Analytics, and Azure Machine Learning

3.  Automate data movement

An Azure subscription can have one or more Azure Data Factory instances (or data factories). Azure Data Factory is composed of four key components.

1.      Pipeline
A data factory can have one or more pipelines. A pipeline is a logical grouping of activities that performs a unit of work.

2.      Activity
Activities represent a processing step in a pipeline. Azure Data Factory supports three types of activities: data movement activities, data transformation activities, and control activities.

3.      Datasets
Datasets represent data structures within the data stores that are used in activities as inputs or outputs.

4.      Linked services

Linked services are much like connection strings. Linked service can represent a data store in case of data movement activity or compute resource in case of data transformation / analysis.

To create a data factory, Click New

Different options to create a data factory:

See Also: 

No comments: