Core Concepts in azure data factory

Dec 9, 2022Download as PPTX, PDF0 likes365 views

Azure Data Factory uses linked services to connect resources, datasets to define data structures, and pipelines containing activities to perform tasks on data. Key concepts include linked services to store connection strings, datasets that point to input/output data, data flows for visual data transformations without code, activities that take datasets as input/output, pipelines that group/manage activities, and triggers that determine when pipelines execute.

Azure Data Factory
2- Main Core Concepts in Azure Data Factory
Welcome in Cloud Learning in Hindi
1

Top core concepts in azure data factory
Welcome in Cloud Learning in Hindi 2
 Linked Services
 Data Sets
 Data Flows
 Activities
 Pipelines
 Trigger

Azure Data Factory
Linked Services:
Welcome in Cloud Learning in Hindi 3
Linked services are used to connect other resources with Azure Data Factory, Linked
service like connection string to connect any resources with azure data factory .A
linked service will store the connection string. Linked Service is a connection to a
data source and/or destination.

Azure Data Factory
Data Sets:
Welcome in Cloud Learning in Hindi 4
Datasets represent data structures within the data stores, which simply points the
data you want to use in your activities as inputs or outputs.
An activity takes a zero or more datasets as inputs and one or more datasets as
outputs.
Example, an Azure Blob dataset specifies the blob container and folder in the Azure
Blob Storage from which the pipeline should read the data. Or, an Azure SQL Table
dataset specifies the table to which the output data is written by the activity.

Azure Data Factory
Data Flow:
Welcome in Cloud Learning in Hindi 6
Data flows are visually designed data transformations in Azure Data Factory. Data
flows allow data engineers to develop data transformation logic without writing code
An activity takes a zero or more datasets as inputs and one or more datasets as
outputs.

Azure Data Factory
Activities:
Welcome in Cloud Learning in Hindi 8
The activities in a pipeline define actions to perform on your data.
For example, you may use a copy activity to copy data from SQL Server to an Azure
Blob Storage. Then, use a data flow activity or a Databricks Notebook activity to
process and transform data from the blob storage to an Azure Synapse Analytics pool
on top of which business intelligence reporting solutions are built.

Azure Data Factory
Pipelines:
Welcome in Cloud Learning in Hindi 9
A pipeline is a logical grouping of activities that together perform a task.
For example, a pipeline could contain a set of activities that ingest and clean log
data, and then kick off a mapping data flow to analyze the log data. The pipeline
allows you to manage the activities as a set instead of each one individually. You
deploy and schedule the pipeline instead of the activities independently.

Azure Data Factory
Trigger:
Welcome in Cloud Learning in Hindi 10
Trigger determines when a pipeline execution needs to be kicked off.

Thank You
Welcome in Cloud Learning in Hindi 11

Azure Data Factory is a cloud-based data integration service that orchestrates and automates the movement and transformation of data. Key concepts in Azure Data Factory include pipelines, datasets, linked services, and activities. Pipelines contain activities that define actions on data. Datasets represent data structures. Linked services provide connection information. Activities include data movement and transformation. Azure Data Factory supports importing data from various sources and transforming data using technologies like HDInsight Hadoop clusters.

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Core Concepts in azure data factory

1. Azure Data Factory 2- Main Core Concepts in Azure Data Factory Welcome in Cloud Learning in Hindi 1

2. Top core concepts in azure data factory Welcome in Cloud Learning in Hindi 2  Linked Services  Data Sets  Data Flows  Activities  Pipelines  Trigger

3. Azure Data Factory Linked Services: Welcome in Cloud Learning in Hindi 3 Linked services are used to connect other resources with Azure Data Factory, Linked service like connection string to connect any resources with azure data factory .A linked service will store the connection string. Linked Service is a connection to a data source and/or destination.

4. Azure Data Factory Data Sets: Welcome in Cloud Learning in Hindi 4 Datasets represent data structures within the data stores, which simply points the data you want to use in your activities as inputs or outputs. An activity takes a zero or more datasets as inputs and one or more datasets as outputs. Example, an Azure Blob dataset specifies the blob container and folder in the Azure Blob Storage from which the pipeline should read the data. Or, an Azure SQL Table dataset specifies the table to which the output data is written by the activity.

5. Welcome in Cloud Learning in Hindi 5

6. Azure Data Factory Data Flow: Welcome in Cloud Learning in Hindi 6 Data flows are visually designed data transformations in Azure Data Factory. Data flows allow data engineers to develop data transformation logic without writing code An activity takes a zero or more datasets as inputs and one or more datasets as outputs.

7. Welcome in Cloud Learning in Hindi 7

8. Azure Data Factory Activities: Welcome in Cloud Learning in Hindi 8 The activities in a pipeline define actions to perform on your data. For example, you may use a copy activity to copy data from SQL Server to an Azure Blob Storage. Then, use a data flow activity or a Databricks Notebook activity to process and transform data from the blob storage to an Azure Synapse Analytics pool on top of which business intelligence reporting solutions are built.

9. Azure Data Factory Pipelines: Welcome in Cloud Learning in Hindi 9 A pipeline is a logical grouping of activities that together perform a task. For example, a pipeline could contain a set of activities that ingest and clean log data, and then kick off a mapping data flow to analyze the log data. The pipeline allows you to manage the activities as a set instead of each one individually. You deploy and schedule the pipeline instead of the activities independently.

10. Azure Data Factory Trigger: Welcome in Cloud Learning in Hindi 10 Trigger determines when a pipeline execution needs to be kicked off.

11. Thank You Welcome in Cloud Learning in Hindi 11

Core Concepts in azure data factory

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