Azure Data Factory Online Training

About Azure Data Factory Online Training

What is Azure Data Factory?

Azure Data Factory (ADF) is a fully managed serverless data integration solution to ingest, prepare and transform all your data at scale. This allows any organization in any industry to use it for a wide range of applications: data engineering, migration of their on-premises SSIS packages to Azure, operational data integration, analytics, data ingestion in data warehouses, and more.

If you have multiple SQL Server Integration Services (SSIS) packages for on-premises data integration, those SSIS packages will run as they do in Azure Data Factory (including custom SSIS components). This allows any developer to use Azure Data Factory for enterprise data integration.

Benefits of Azure Data Factory

  • Azure Data Factory is a cloud-based service that is used to manage the copying of data between various relational and non-relational data sources hosted in the cloud or on-premises in your data centre and transform them to meet business needs. It is a big data service responsible for cloud-based fetch, transform and load (ETL), fetch, load, and transform (ELT) and process data retrieval using scheduled data-driven workflows. 

Azure Data Factory by iSofttrainings designed by experts based on thorough research. Become a certified Azure Data Factory Engineer by grasping dexterities and skills in Azure Data Factory, SQL Database, Azure Cosmos DB, Azure Data Lake Storage, Azure Databricks, Blob Storage, etc.

The following are some of the major advantages of Azure Data Factory:

    • Easy Migration of ETL Workloads to Cloud
    • Code-free Data Transformation
    • Better Scalability & Performance
    • Cost-Efficient Platform
  • Due to the growing demand for Microsoft Azure Engineers in today’s industry, this brilliant certificate resume has great benefits.
  • In terms of job prospects and benefits, the certification resulted in a sharp increase in both.
  • Updating your professional profile with this certificate will elevate your work profile and enhance your employability.
  • Most people agree that certification has increased their income, and 84% of people see better job prospects after certification.

Azure Data Factory Target group

  • IT professionals interested in Azure Data Factory
  • Those who want to implement data flow in their organization.

Learning objectives

  • After completing this course, you will be able to:
  • Review the features, concepts and requirements needed to design a data flow
  • Learn basic data flow principles and common data flow scenarios
  • Learn how to deploy data streams in Microsoft Azure
  • Azure SQL Database, Azure Data Lake, Azure Data Bricks, Azure Data Factory, Azure Monitoring Services, and Azure HD Insights

What will you learn after completion of the course?

Upon successful completion of the Azure Data Factory DP-200 training, participants will be able to:

  • Use data factory and connect Power BI to data pool
  • Data processing design, Azure Data Solutions and data security
  • Apply big data engineering skills in Microsoft cloud services
  • Use Azure Data Service Stacks to manage, monitor, and protect data
  • Take more responsibility in Azure management domain
  • Integrate the enhanced version of Apache Spark with open-source libraries
  • Scale and manage real-time event handling applications
  • Get ready for the Microsoft Azure DP 200 certification exam

Course Content

  • Introduction to cloud computing
  • Why Cloud Computing?
  • Different Cloud Computing Models like SaaS, PaaS and Iaas
  • Understanding Hybrid Cloud
  • How is azure a leader in the cloud market?
  • Importance of Data Warehouse, ETL and Analytics with cloud
  • What is Microsoft Azure Data Factory?
  • Overview of its workflow and different services in it
  • Intro to non-relational data stores
  • Intro to Cosmos DB, Data Lake Storage and Blob Storage
  • Why Cosmos DB?
  • Working with Cosmos DB
  • Implement a solution that uses Cosmos DB
  • Why Data Lake?
  • Working with Data Lake
  • Implement a solution that uses Data Lake Storage Gen2
  • Why Blob Storage?
  • Working with Blob Storage
  • Implement a solution that uses Blob storage
  • Implement data distribution and partitions
  • Implement a consistency model in Cosmos DB
  • Provision a non-relational data store
  • Provide access to data to meet security requirements
  • Understanding High Availability, disaster recovery and global distribution
  • Implement for high availability, disaster recovery, and global distribution
  • Intro to relational database and data stores
  • Understand elastic pools in a data store
  • Configuring elastic pools
  • Configuring geo-replication
  • Provide access to data for meeting the security requirements
  • Implement for high availability, disaster recovery, and global distribution in relational data stores
  • What is Azure Synapse Analytics and why is it important?
  • Implement data distribution and partitions for Azure Synapse Analytics
  • Understanding the relevance of PolyBase
  • Implement PolyBase
  • Understand the data masking
  • Implement data masking
  • Encrypt data at rest and in motion
  • What is Azure Databricks?
  • What is Azure Data Factory?
  • Why Azure Databricks?
  • Why Azure Data Factory?
  • Develop batch processing solutions by using Data Factory and Azure Databricks
  • Understanding the concept behind data ingestion
  • What is PolyBase?
  • Understanding the workflow of PolyBase
  • Ingest data by using PolyBase
  • Implement the integration runtime for Data Factory
  • Implement Copy Activity within Azure Data Factory
  • Create linked services and datasets
  • Create pipelines and activities in Data Factory
  • Implement Mapping Data Flows in Azure Data Factory
  • Create and schedule triggers in Azure Data Factory
  • Implement Azure Databricks clusters, notebooks, jobs, and autoscaling
  • Ingest data into Azure Databricks
  • Creating the whole data lifecycle in Azure Data Factory
  • What is Azure Stream Analytics?
  • Why Azure Stream Analytics?
  • Configure input and output
  • Select the appropriate windowing functions
  • Implement event processing by using Stream Analytics
  • Monitoring in Azure Data Factory
  • What is Azure Monitor?
  • Why use Azure Monitor?
  • Understanding Azure Log Analytics
  • Why Azure Log Analytics?
  • Implement monitoring in Blob Storage
  • Implement monitoring in Data Lake Storage
  • Implement monitoring in SQL Database
  • Implement monitoring in Azure Synapse Analytics
  • Implement monitoring in Cosmos DB
  • Configuring alerts in Azure Monitor
  • Implement auditing by using Azure Log Analytics
  • Monitoring Data Factory pipelines
  • Monitoring Azure Databricks
  • Monitoring Stream Analytics
  • Configuring alerts in Azure Monitor in the data processing
  • Implement auditing by using Azure Log Analytics in the data processing
  • Troubleshoot data partitioning bottlenecks
  • Optimize Data Lake Storage
  • Optimize Stream Analytics
  • Optimize Azure Synapse Analytics
  • Optimize SQL Database
  • Manage the data lifecycle

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We provide the helpful Azure Data Factory tutorial for Beginners, Azure Data Factory training videos and Azure Data Factory interview questions & answers for both fresher and experienced candidates.

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