Get a Complete Step By Step Guide About Azure Data Factory ( ADF ) Training:

Here Below Is Complete Overview About Azure Data Factory Course and if you’re Interested to Learn Azure Data Factory Online Course Training In Hyderabad Simply Call and Get FREE DEMO.

What Is Azure Data Factory ?

Azure Data Factory (ADF) is a cloud data integration service. ADF is utilized to connect diverse data sources across the company, including cloud data and on-premises information. It can make use of computing services such as Azure Hadoop, Spark, Azure Data Lake Analytics along with Azure Machine Learning in order to transform and process the data. You will be taught how to create data-driven pipelines that control the movement of data In Azure Data Factory Training in Hyderabad.


Azure Data Factory (ADF) is a cloud-based service that allows data integration. ADF can be used to connect different data sources across the company, which includes cloud-based data and data stored on premises. It is able to transform and process data through compute-related services such as Azure Hadoop, Spark, Azure Data Lake Analytics as well as Azure Machine Learning.

The Azure Data Factory Professional certification is overseen by the International Azure Data Factory Certification Consortium. Its Azure Data Factory training focuses on teaching the fundamental elements of information security through intensive learning sessions as well as practical examples. Its Azure Data Factory certification training will help you understand and demonstrate your knowledge of system security across the eight domains that comprise the Azure Data Factory Course. 

It provides you with global recognition in the area that is Azure Data Factory and also provides the opportunity to work for corporate giants. It is an Azure Data Factory course will help you become the Azure Data Factory specialist who is current with the current security standards and will help in the creation of a reliable and flexible security program which is compliant with regulations set by the government.

Features of Azure Data Factory:-

It’s extremely simple to use, as it can redirect SQL Server Integration Services (SSIS) with just only a few clicks, and also build ETL or ELT pipelines with no code, thanks to integrated Git as well as CI/CD compatibility.

* Azure Data Factory is cost-effective as it offers pay-as-you go, fully-controlled cloud service with no server that can scale according to the need.

* It is able to consume every single on-premises, as well as software as the service (SaaS) information using more than 90 built-in connectors. to organize and analyze data at a size.

Course Summary:

This certification course was developed by our certified professionals for Professionals and Beginners. Do you want to be the best of the Azure data Factory ? If so, you’d like to be certified. This is a real-time simulation with a based certification, and an Industry-approved course. A cloud-based service for data integration allows you to create data-driven workflows using the cloud. It is possible to create and plan data-driven workflows.

Learn about the Azure Data Factory, Basics of data flows and Data flow scenarios. the life cycle of data, Azure data lake storage how to set up non-relational data stores Partitions and distribution of data, Data Lake Storage, Data Security using Azure Data Factory, Azure Databricks, and how to implement Integration runtime, Mapping Data Flows Azure Stream Analytics, Azure Log Analytics How to monitor Data Factory pipelines, Azure Databricks as well as Stream Analytics, Troubleshoot data bottlenecks in partitioning, and managing the lifecycle of data.

What Activities Are There In Azure Data Factory ?

Copy Activity – Copy Data From Many Supported Sources Both on-Premise and Cloud Sources.

Transform Activity -Transform the Data.

Monitor Activity – Monitor the Data Flows Using a Rich Graphical Interface.

Publish Activity – Publish The Transformed and Copied Data, Sending it To a Destination Data Storage or Analytical Engine.

Why Do I Need To Use Azure Data Factory?

Data Factory is used For all Cloud Related Projects. Nearly every cloud project must perform activities to move data across Various Networks. Data Factory is a Particularly required enabler for companies who are taking their first steps into the cloud and are therefore trying connecting on-premise data with the cloud.

Criteria for eligibility

Work Experience:

It is suggested that participants of the course have an experience of work with Azure Data Lake, Azure SQL Data Warehouse, Azure Stream Analytics as well as Azure Data Factory.

Certification Qualifying Details:

Participants must succeed in completing the course through real-world assignments and passing quizzes, assignments and tests. The test will assist students to do better on the certification test.

Participants need to score an average of 60% in the certification test and finish each of the assignments (reviewed by experts) in order to receive the E Meta Trainings Course Completion Certificate. It is the E Meta Trainings Certificate is recognized from more than 80 multinational corporations around the globe, as well as some Fortune 500 companies.

Participants who are qualified will also be awarded an Microsoft certificate on “Performing Big Data Engineering on Microsoft Cloud Services’.

Who Is this Azure Data Factory Course For ?

This Azure Data Factory training course for DP-203 program online is perfect for the following purposes:

  • Data Analysts
  • Data Scientist
  • Data Architects
  • Data Engineers
  • Students who design analytics solutions
  • Professionals who build operational solutions for Azure
  • People who have a working understanding of real-time processing, operationalization and batch data processing technology

What Azure Data Factory can do?

Azure Data Factory allows companies to transform rational and non-rational data into essential strategies. This is accomplished by integrating big data with workflows that are driven by data, called pipelines. This allows companies to improve the value for their own organizations, and to attaining their goals. This course offered delivered by E Meta Trainings will aid the participants in enhancing their roles regarding their role in the Azure Administration domain.

In the course of working on real-world tasks during the training participants will have the chance to demonstrate their abilities in real-world scenarios. The successful success in these real-world tasks will help the students be ready for the workplace. The participants of the course will be able to enhance their capabilities in relation to Azure Data Factory, Azure Stream Analytics, Microsoft Azure SQL Data Warehouse along with Azure Data Lake Analysis. They will be able to integrate data using Hive and copying data through Spark.

In addition to enhancing skills and imparting deep learning, E Meta Trainings will also assist those who attend Azure Data Factory Training DP-203 in application and resume process. The assistance with placement provided by E Meta Trainings will give the opportunity to the students to research opportunities that they like in MNCs and Fortune 500 companies.

Azure Data Factory Course Content:

Azure Data Factory: an Introduction

  • Overview
  • Introduction to Azure Data Factory
  • What’s New in Azure Data Factory

Create data factory – User interface (UI)

  • Prerequisites
  • Azure Storage account
  • Create a data factory
  • Create a linked service
  • Create datasets
  • Create a pipeline
  • Debug the pipeline
  • Trigger the pipeline manually
  • Monitor the pipeline
  • Trigger the pipeline on a schedule

Create data factory – Copy data tool

  • Prerequisites
  • Azure subscription
  • Azure roles
  • Azure Storage account
  • Create a data factory
  • Start the Copy Data tool

Create an Azure Data Factory using Azure CLI

  • Prerequisites
  • Prepare a container and test file
  • Create a data factory
  • Create a linked service and datasets
  • Create and run the pipeline
  • Clean up resources

Create an Azure Data Factory using PowerShell

  • Prerequisites
  • Azure Storage account
  • Azure PowerShell
  • Create a data factory
  • Create a linked service
  • Create datasets
  • Create a pipeline
  • Create a pipeline run
  • Monitor the pipeline run
  • Review deployed resources
  • Clean up resources

Create a data factory and pipeline using .NET SDK

  • Prerequisites
  • Create an application in Azure Active Directory
  • Create a Visual Studio project
  • Install NuGet packages
  • Create a data factory client
  • Create a data factory
  • Create a linked service
  • Create a dataset
  • Create a pipeline
  • Create a pipeline run
  • Monitor a pipeline run
  • Run the code

Create a data factory and pipeline using Python

  • Prerequisites
  • Create and upload an input file
  • Install the Python package
  • Create a data factory client
  • Create a data factory
  • Create a linked service
  • Create datasets
  • Create a pipeline
  • Create a pipeline run
  • Monitor a pipeline run
  • Full script
  • Run the code
  • Clean up resources

Create an Azure data factory and pipeline by using the REST API

  • Prerequisites
  • Set global variables
  • Authenticate with Azure AD
  • Create a data factory
  • Create linked services
  • Create datasets
  • Create a pipeline
  • Create pipeline run
  • Parameterize your pipeline
  • Create parameterized input dataset
  • Create parameterized output dataset
  • Create parameterized pipeline
  • Create pipeline run with parameters
  • Monitor pipeline
  • Verify the output
  • Clean up resources

Create an Azure Data Factory using ARM template

  • Prerequisites
  • Review template
  • Deploy the template
  • Review deployed resources
  • Clean up resources

Copy and ingest data

  • Copy data tool
  • Copy activity in pipeline
  • Copy data from on-premises to the cloud
  • Amazon S3 to ADLS Gen2
  • Incremental copy pattern overview
  • Incremental pattern with change tracking
  • Incremental SQL DB single table
  • Incremental SQL DB multiple tables
  • CDC copy pipeline with SQL MI
  • Copy from SQL DB to Synapse SQL Pools
  • Copy SAP BW to ADLS Gen2
  • Copy Office 365 to Azure Blob Store
  • Bulk copy multiple tables
  • Copy pipeline with managed VNet

Transform Data

  • Transform Data with Mapping Data Flows
  • Prepare data with data wrangling
  • Using External Services
  • Control Flow
  • Run SSIS Packages in Azure
  • Lineage
  • End to end Labs
  • Managed Virtual Networks
  • Self-hosted integration runtime

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