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    ADF Notes

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    Bharath
    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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    ADF Notes

    Uploaded by

    Bharath
    20 views1 page
    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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    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.

    Copyright:

    © All Rights Reserved
    Download as TXT, PDF, TXT or read online from Scribd
    Download as txt, pdf, or txt
    20 views1 page

    ADF Notes

    Uploaded by

    Bharath
    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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    © All Rights Reserved
    Download as TXT, PDF, TXT or read online from Scribd
    Download as txt, pdf, or txt
    of 1

    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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