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azure data factory training

Azure Data Factory is a cloud-based data integration service provided by Microsoft Azure. It is designed to help organizations create, schedule, and automate data workflows, allowing for the efficient movement and transformation of data between various data stores and processing systems.

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Duration of Training  :  32 hrs

Batch type  :  Weekdays/Weekends

Mode of Training  :  Classroom/Online/Corporate Training


Azure Data Factory Training & Certification in Pune

Highly Experienced Certified Trainer with 10+ yrs Exp. in Industry

Realtime Projects, Scenarios & Assignments



This Certification course has been designed by our certified professional for Beginners’ and Professionals. Want to become the master in Azure data Factory and would like to certify. This is a Real-time scenario based certification and Industry Endorsed course. A cloud-based data integration service allows creating data-driven workflows in the cloud. You can create and schedule data-driven workflows.

You will learn Introduction to Azure Data Factory, Basics of data Flows, Data flow scenarios, Data life cycle, Azure data lake storage, How to implement non-relational Data Stores, Data distribution and partitions, Data Lake Storage, Data Security with Azure Data Factory, Azure Databricks, how to Implement integration runtime, Mapping Data Flows, Azure Stream Analytics, Azure Log Analytics, how to Monitoring Data Factory pipelines, Azure Databricks, and Stream Analytics, Troubleshoot data partitioning bottlenecks, how to manage the data lifecycle.

Introduction to Cloud Computing and Azure data Factory :

  • Cloud Computing and cloud computing models like SaaS, PaaS and Iaas
  • Hybrid Cloud
  • Data Warehouse, ETL and Analytics with cloud
  • Microsoft Azure Data Factory
  • Azure Data Factory workflow and different services

Implement non-relational data stores :

  • Intro to non-relational data stores
  • Cosmos DB
  • Data Lake Storage
  • Blob Storage
  • Data Lake
  • Blob Storage
  • Data distribution and partitions
  • Consistency model in Cosmos DB
  • High Availability, disaster recovery and global distribution

 Implement relational data stores :

  • Relational database and data stores
  • Relational data stores
  • High availability, disaster recovery, and global distribution
  • Elastic pools in a data store
  • Geo-replication
  • Azure Synapse Analytics
  • Data distribution and partitions for Azure Synapse Analytics
  • Relevance of PolyBase

Manage Data Security :

  • Introduction to Data Security with Azure Data Factory
  • Data masking
  • Use of Data Masking 

Develop batch processing solutions :

  • Azure Databricks
  • Azure Data Factory
  • Batch processing solutions using Data Factory and Azure Databricks
  • Data ingestion
  • PolyBase and workflow of PolyBase
  • Ingest data using PolyBase
  • Implement integration runtime
  • Implement Copy Activity
  • Linked services and datasets
  • Pipelines and activities
  • Mapping Data Flows
  • Azure Databricks clusters, notebooks, jobs, and auto scaling
  • Ingest data into Azure Databricks

Develop streaming solutions :

  • Azure Stream Analytics
  • Configure input and output
  • Select the appropriate windowing functions
  • Implement event processing by using Stream Analytics

Monitor relational and non-relational data sources :

  • Introduction to monitoring in Azure Data Factory
  • Azure Monitor
  • Azure Log Analytics
  • Monitoring in Blob Storage and Data Lake Storage
  • Monitoring in SQL Database and Azure Synapse Analytics, and Cosmos DB
  • Configuring alerts in Azure Monitor
  • Auditing by using Azure Log Analytics

Monitor data processing :

Monitoring Data Factory pipelines

Azure Databricks

Stream Analytics

Configuring alerts in Azure Monitor

Auditing by using Azure Log Analytics

Optimize Azure data solutions :

  • Troubleshoot data partitioning bottlenecks
  • Optimize Data Lake Storage, Stream Analytics, Synapse Analytics, and SQL Database
  • Manage the data lifecycle

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