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
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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 and Azure Data Factory

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

Implement non-relational data stores

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

Implement relational data stores

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

Manage data security

Understand the data masking
Implement data masking
Encrypt data at rest and in motion

Develop batch processing solutions

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

Develop streaming solutions

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

Monitor relational and non-relational data sources

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

Monitor data processing

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

Optimize Azure data solutions

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 are committed to providing you the AAzure Data Factory Online Training and placement in USA, Canada, Hyderabad and Bangalore.

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.

List of Courses

About this course:

Method

Led Training

Type

Online

Schedules

Flexible Schedules

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