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ADF Course Training in Hyderabad

Aim Technologies is one of the Leading Azure Data Factory Training institute in Hyderabad, offers 100% placement-oriented with real-world projects, we are one of the best Training Institute in Hyderabad that provides Industry Level Training with Real Time Projects.

FEATURES OF TABLEAU:
  • Easy SSIS migration
  • Large collection of data collectors
  • No-code data workflows
  • Built-in monitoring and alerting

Azure Data Factory Course Curriculum

  • Creating an Azure Data Factory Instance
  • Get Started in Azure
  • Create a Free Azure Account
  • Explore the Azure Portal
  • Create a Resource Group
  • Create an Azure Data Factory
  • Explore the Azure Data Factory User
  • Experience
  • Navigation Header Bar
  • Navigation Sidebar
  • Link to a Git Repository
  • Create a Git Repository in Azure Repos
  • Link the Data Factory to the Git Repository
  • The ADF UX as a Web-Based IDE
  • Introduction
  • Work with Azure Storage
  • Create an Azure Storage Account
  • Explore Azure Storage
  • Upload Sample Data
  • Use the Copy Data Tool
  • Explore Your Pipeline
  • Linked Services
  • Datasets
  • Pipelines
  • Activities
  • Integration Runtimes
  • Factory Resources in Git
  • Debug Your Pipeline
  • Run the Pipeline in Debug Mode
  • Inspect Execution Results
  • The Copy Data Activity
  • Prepare an Azure SQL Database
  • Create the Database
  • Create Database Objects
  • Import Structured Data into Azure SQL DB
  • Create the Basic Pipeline
  • Process Multiple Files
  • Truncate Before Load
  • Map Source and Sink Schemas
  • Create a New Source Dataset
  • Create a New Pipeline
  • Configure Schema Mapping
  • Import Semi-structured Data into Azure SQL
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  • DB
  • Create a JSON File Dataset
  • Create the Pipeline
  • Configure Schema Mapping
  • Set the Collection Reference
  • The Effect of Schema Drift
  • Understanding Type Conversion
  • Transform JSON Files into Parquet
  • Create a New JSON Dataset
  • Create a Parquet Dataset
  • Create and Run the Transformation Pipeline
  • Performance Settings
  • Data Integration Unit
  • Degree of Copy Parallelism
  • Azure Data Factory User Experience (ADF
  • UX)
  • Explore the Expression Builder
  • Use System Variables
  • Enable Storage of Audit Information
  • Create a New Pipeline
  • Add New Source Columns
  • Run the Pipeline
  • Access Activity Run Properties
  • Create Database Objects
  • Add Stored Procedure Activity
  • Run the Pipeline
  • Use the Lookup Activity
  • Create Database Objects
  • Configure the Lookup Activity
  • Use Breakpoints
  • Use the Lookup Value
  • Update the Stored Procedure Activity
  • Run the Pipeline
  • User Variables
  • Create a Variable
  • Set a Variable
  • Use the Variable
  • Array Variables
  • Concatenate Strings
  • Infix Operators
  • String Interpolation
  • Escaping @
  • Set Up an Azure Key Vault
  • Create a Key Vault
  • Create a Key Vault Secret
  • Grant Access to the Key Vault
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  • Divert Error Rows
  • Load Error Rows
  • Understand the Switch Activity
  • Use Iteration Activities
  • Use the Get Metadata Activity
  • Use the ForEach Activity
  • Ensure Parallelizability
  • Understand the Until Activity
  • Build a Data Flow
  • Enable Data Flow Debugging
  • Add a Data Flow Transformations
  • Aggregate Transformation
  • Alter row Transformation
  • Assert Transformation
  • Conditional split Transformation
  • Derived column Transformation
  • External call Transformation
  • Exists Transformation
  • Filter Transformation
  • Flatten Transformation
  • Join Transformation
  • Lookup Transformation
  • New branch Transformation
  • Parse Transformation
  • Pivot Transformation
  • Rank Transformation
  • Select Transformation
  • Sink Transformation
  • Sort Transformation
  • Source Transformation
  • Stringify Transformation
  • Surrogate key Transformation
  • Union Transformation
  • Unpivot Transformation
  • Window Transformation
  • Execute the Data Flow
  • Azure Integration Runtime
  • Inspect the AutoResolveIntegrationRuntime
  • Create a New Azure Integration Runtime
  • Use the New Azure Integration Runtime
  • Self-Hosted Integration Runtime
  • Create a Shared Data Factory
  • Create a Self-Hosted Integration Runtime
  • Link to a Self-Hosted Integration Runtime
  • Use the Self-Hosted Integration Runtime
  • Azure-SSIS Integration Runtime
  • Create an Azure-SSIS Integration Runtime
  • Deploy SSIS Packages to the Azure-SSIS IR
  • Run an SSIS Package in ADF
  • Stop the Azure-SSIS IR
Download Azure Data Factory Course Syllabus

Frequently Asked Questions

Does Azure Data Factory require coding?

Any developer may speed up the creation of data transformations using code-free data flows thanks to Azure Data Factory. Any developer can create data transformation without writing any code by using the ADF Studio.

What is Azure Data Factory mainly used for?

Oracle ADF is appropriate for enterprise developers who want to construct applications that use online, mobile, and desktop interfaces to search, display, create, change, and validate data.

Is Azure Data Factory difficult to learn?

The exception-handling system in Azure Data Factory presents the sole difficulty. It is challenging to detect and log record failures.

Can I attend a demo session before enrollment?

Yes you can attend a free demo lecture.

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