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Azure Data Factory course training in Hyderabad [ADF]

It is a cloud service that allows you to store, manage and analyze data from your applications. The service is based on the Azure SQL Database, which is one of the most popular relational databases in the world.
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What Is Azure Data Factory ?

Azure Data Factory is a cloud service that allows you to store, manage and analyze data from your applications. The service is based on the Azure SQL Database, which is one of the most popular relational databases in the world.

Or,

Azure Data Factory is a service that can be used to create, manage and maintain data pipelines. It is a Microsoft product that provides automation for data processing workflows, Azure Data Factory is a data processing engine that can be used to create and run complex, transactional workloads. 

What Is Azure Data Factory ?

Azure Data Factory is a cloud service that allows you to store, manage and analyze data from your applications. The service is based on the Azure SQL Database, which is one of the most popular relational databases in the world.

Or,

Azure Data Factory is a service that can be used to create, manage and maintain data pipelines. It is a Microsoft product that provides automation for data processing workflows, Azure Data Factory is a data processing engine that can be used to create and run complex, transactional workloads. 

ADF Training In Hyderabad & Bangalore

Advantages Of Azure Data Factory Training in Hyderabad

  • Azure Data Factory provides an easy way to monitor and manage your data pipelines.
  • In addition to SQL, Azure Data Factory supports a variety of Azure services and integrations.
  • The service is compatible with many popular databases, including Azure SQL and CosmosDB.
  • The service can be used to connect and manage data sources on the cloud and on premises.
  • Azure Data Factory supports both batch and streaming data processes.
  • It also has built-in support for SSIS, an ETL tool.

Benefits Of Learn Azure Data Factory:

  • It Is Easy To Learn Even If You’re a Fresher.
  • You Get The Job In The Software Industry In Less Than 90 Days.
  • No Coding Language Required To Learn.
  • You Get Decent Package 
  • Good Career Choice Why Because It’s Cloud Technology 

Why Azure Data Factory With Vinay Tech House:-

A comprehensive training resource that includes real-time training scenarios for every area of study using the Azure Data Factory Training solutions.

* We also provide cases studies to support MSBI training.

* We plan sessions according to your preferences by highly skilled and trained experts in real-time.

* We record a session to be used for reference in the future.

* We also offer an ongoing, quick and weekend-long course to provide the online MSBI Training.

* We also offer lucrative and flexible payment plans that are flexible and profitable.

Course Highlights
Live Projects
Placement Assistance
Expert Trainers
Premium Training
Flexible Timings
Real-Time Case Studies

Frequently Asked Questions

Quick Enquiry
Future Scope of a Career in   ADF
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In-Depth Curriculum

Our educational program aims to comprehensively cover all & important points & aspects of the subject

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10+ Years of Experience

We’ve come a long way teaching from hundreds to thousands, so we use our experience in guiding students in the right path

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Course Specialized Trainers

Our Trainers are high experienced industry experts with their teaching methods designed for their particular course

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Vinay Tech House is prefered by many students as their favourite, rating as the best in teaching

Curriculum
  • What is the “Cloud”?

  • Why cloud services

  • Types of cloud models

  • Deployment Models

    • Private Cloud deployment model

    • Public Cloud deployment model

    • Hybrid cloud deployment model

  • Characteristics of cloud computing

    • On-demand self-service

    • Multi-tenancy and resource pooling

    • Measured service

  • Cloud Data Warehouse Architecture

    • Shared Memory architecture

    • Shared Disk architecture

    • Shared Nothing architecture

  • Core Azure Architectural components

  • Core Azure Services and Products

  • Azure solutions

  • Azure management tools

  • DWH Life Cycles

    • DWH Approaches (INMON and KIMBALL)

    • Data Granularity, Data movement stages

  • Azure subscriptions

  • Planning and managing costs

  • Azure support options

  • Azure Service Level Agreements (SLAs)

  • Service Lifecycle in Azure

  • Introduction Azure SQL Database

  • Comparing Single Database

  • Managed Instance

  • Creating and Using SQL Server

  • Azure SQL Database Tools

  • Migrating on premise database to SQL Azure

  • Purchasing Models

    • DTU service tiers

    • vCore based Model

    • Server-less compute tier

  • Service Tiers

    • General purpose / Standard

    • Business Critical / Premium

    • Hyperscale

  • Deployment of an Azure SQL Database

  • What is SQL elastic pools

    • Choosing the correct pool size

    • Creating a New Pool

    • Manage Pools

  • Monitoring and Tuning Azure SQL Database

  • Configure SQL Database Auditing

  • Export and Import of Database

  • Storage Service and Account

  • Creating a Storage Account

  • Standard and Premium Performance

  • Understanding Replication

  • Hot, Cold and Archive Access Tiers

  • Working with Containers and Blobs

  • Types of Blobs

    • Block Blobs

    • Append Blobs

    • Page Blobs

  • Blob Metadata

  • Soft Delete

  • Azure Storage Explorer

  • Access blobs securely

    • Access Key

    • Account Shared Access Token

    • Service Shared Access Token

    • Shared Access Policy

  • Storage Service Encryption

  • Azure Key Vault

  • What is Data Factory?

  • Data Factory Key Components

    • Pipeline

    • Activity

    • Linked Service

    • Data Set

    • Integration Runtime

    • Triggers

    • Data Flows

  • Page Blobs

  • Integration Runtime Provision Required Azure Resources

    • Create Resource Group

    • Create Storage Account

    • Provision SQL Server and Create Database

    • Provision Azure Data Factory (ADF) Service

  • Understanding Data Factory UI

  • Copy Data from Blob Storage to SQL Database

  • Copy data from storage account to storage account

  • Create Linked Service and Create Dataset

  • Create Pipeline – Integration Service

  • Copy Data from on-premise SQL Server to Blob Storage

  • Working with Activities

    • Understanding Lookup Activity

    • Understanding For Each Activity

    • Filter Activity

    • Get Metadata Activity

  • Azure Lift and Shift

  • Provisioning Azure – SSIS Integration Runtime

  • Execute SSIS Packages from Azure

  • Execute SSIS Packages from SSISDB

  • Triggers

  • Monitoring Pipeline

    • Debug Pipeline

    • Trigger pipeline manually

    • Monitor pipeline

    • Trigger pipeline on schedule

  • ADF Introduction

  • Important Concepts in ADF

  • Create Azure Free Account for ADF

  • Integration Runtime and Types

    • Integration Runtime in ADF – Azure IR

  • Create Your First ADF

  • Create Your First Pipeline in ADF

  • Azure Storage Account Integration with ADF

  • Copy multiple files from blob to blob

  • Filter activity – Dynamic Copy Activity

  • Get File Names from Folder Dynamically

  • Deep dive into Copy Activity in ADF

    • Copy Activity Behavior in ADF

    • Copy Activity Performance Tuning in ADF

  • Validation in ADF

    • Get Count of files from folder in ADF

    • Validate copied data between source and sink in ADF

  • Azure SQL Database integration with ADF

    • Azure SQL Databases – Introduction to Relational Databases

    • Creating Your First Azure SQL Database

    • Deployment Models

    • Purchasing Modes

  • Overwrite and Append Modes in Copy Activity

  • Full Load in ADF

  • Copy Data from Azure SQL Database to BLOB in ADF

  • Copy multiple tables in bulk with Lookup & ForEach in Data Factory

  • Logging and Notification – Azure Logic Apps

    • Log Pipeline Executions to SQL Table using ADF

    • Custom Email Notifications – Send Error Notification with Logic App

  • Use Foreach Loop Activity to Copy Multiple Tables – Step-by-Step Explanation

  • Incremental Load in ADF

    • Incremental or Delta Load from SQL to Blob Storage

    • Multi-table Incremental Load or Delta Load

    • Incrementally Copy New and Changed Files Based on Last Modified Date

  • Azure Key Vault Integration with ADF

    • Secure secrets, keys & certificates in Azure Data

  • ADF Triggers

    • Event-Based Trigger

    • Tumbling Window Trigger – Dependency & Parameters

    • Schedule Trigger

  • Self-Hosted Integration Runtime

    • Copying On-Premise Data Using Azure Self-Hosted IR

    • Data Migration from On-Premise SQL Server to Cloud

    • Load Data from On-Premise SQL Server to Azure SQL DB

    • Data Migration with PolyBase and Bulk Insert

    • Copy Data from SQL Server to Azure SQL DW with PolyBase & Bulk Insert

    • Data Migration from On-Premise File System to Cloud

    • Copy Data from On-Premise File System to ADLS Gen2

  • Copying Data from REST API using ADF

    • Loop Through REST API – Copy Data to ADLS Gen2

    • Linked Service Parameters

  • AWS S3 Integration with ADF

    • Migrate Data from AWS S3 Buckets to ADLS Gen2

  • Activities in ADF

    • Switch Activity – Move and Delete Data

    • Until Activity – Parameters & Variables

    • Copy Recent Files from Blob Input to Blob Output Folder Without LPV

  • Snowflake Integration with ADF

    • Copy Data from Snowflake to ADLS Gen2

    • Copy Data from ADLS Gen2 to Snowflake

  • Azure CosmosDB Integration with ADF

    • Copy Data from Azure SQL DB to CosmosDB

    • Copy Data from Blob to CosmosDB

  • Advanced Concepts in ADF

    • Nested ForEach – Pass Parameters from Master to Child Pipeline

    • High Availability of Self-Hosted IR & Sharing IR with Other ADFs

  • Data Flows Introduction

    • Azure Data Flows Introduction

    • Setup Integration Runtime for Data Flows

    • Basics of SQL Joins for Azure Data Flows

    • Joins in Data Flows

    • Aggregations and Derive Column Transformations

    • Advanced Join Transformations with Filter and Conditional Split

    • Data Flows – Data Processing Use Case 1

    • Restart Data Processing from Failure

    • Remove Duplicate Rows & Store Summary Credit Stats

    • Difference Between Join vs. Lookup Transformation & Merge Functionality

    • Dimensions in Data Flows

    • Slowly Changing Dimension Type 1 (SCD1) with HashKey Function

    • Flatten Transformation

    • Rank, Dense_Rank Transformations

    • Data Flows Performance Metrics and Parameters

    • How to Use Pivot and Unpivot Transformations

    • Data Quality Checks and Logging Using Data Flows

  • Batch Account Integration with ADF

  • Custom Activity in ADF

  • Azure Functions Integration with ADF

  • Azure Databricks Integration with ADF

  • ADF Integration with Azure Databricks

  • Azure Data Lake Analytics Integration with ADF

  • Introduction to Databricks

  • Azure Databricks Architecture

  • Azure Databricks Main Concepts

  • Databricks Integration with Azure Blob Storage

    • Read Data from Blob Storage

    • Create Blob Mount Point

  • Features of Python

  • Python Virtual Machine (PVM)

  • Frozen Binaries

  • Memory Management in Python

  • Garbage Collection in Python

Projects Covered

Banking Project

We Do Cover Microsoft Azure Project In Our Training That Helps You Give Real Time Experience.

Telecommunications project

This project helps you get real-time experience into the Azure workflow

Interested in a Free demo? Want to learn more?
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