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ADF Notes

Azure Data Factory helps analyze, transform, and store large amounts of data from different sources by using pipelines to move data through stages. It stores data in Azure Data Lake Storage, analyzes and transforms the data using pipelines, and publishes the organized data for visualization by third parties. The data flows from input datasets through a pipeline to output datasets, using linked services to connect to storage and SQL, with a gateway enabling on-premises connections to the cloud.

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1K views1 page

ADF Notes

Azure Data Factory helps analyze, transform, and store large amounts of data from different sources by using pipelines to move data through stages. It stores data in Azure Data Lake Storage, analyzes and transforms the data using pipelines, and publishes the organized data for visualization by third parties. The data flows from input datasets through a pipeline to output datasets, using linked services to connect to storage and SQL, with a gateway enabling on-premises connections to the cloud.

Uploaded by

Bharath
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as TXT, PDF, TXT or read online on Scribd
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Azure Data Factory:

*******************

As data is coming from a no of different products, to analyze and store all this
data, we need a powerful (Azure Data Factory) helps us here by:

1-->Storing data with help of Azure Data Lake Storage


2-->Analyzing the data
3-->Transforming the data with the help of pipelines(logical grouping of activities
that together perform a task)
4-->Publishing the organized data
5-->Visualizing the data with third-party applications like Apache Spark/Hadoop

Flow process of Data Factory:

Input Dataset ==> Pipeline ==> Output Dataset==> Linked Services ==> Azure Data
Lake & Block Storage & SQL ==> Gateway ==> Cloud.

Input Dataset: Data that we have within our data store. We need it to be processed,
so we pass this data through a pipeline.

PipelIne: performs an operation on the data that transforms data,which could be


anything

Output Dataset: contains the data that is in s

Linked Services: Store information that is very important when it comes to


connecting to an external source.

Gateway: It Connects our on-premises data to the cloud. system so that we can
connect to Azure cloud

Cloud: Our

ADF Components:

1. Activity ---> Copy, Delete

2.DATASET ---> This is pointing to file

3.Linked Service --> Connection

4.Integration Run Time --> 1.Auto Resolve


2.Self Hosted
3.SSIS

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