Azure Data
Factory, a cloud data integration service using that we can
To create a data factory, Click New
Different options to create a data factory:
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.
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