Azure Data Engineering Corporate Training Course

Azure Data Engineer instructor-led training course equips teams with the skills needed to design, build, and manage strong data solutions on Microsoft's Azure platform. This training prepares professionals to tackle the challenges of data management and analytics in a cloud-based environment.

24 - 32 hrs
Instructor-led (On-site/Virtual)
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Azure Data Engineering Training
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Drive Team Excellence with Azure Data Engineering Corporate Training

On-site or Online Azure Data Engineering Training - Get the best Azure Data Engineering training from top-rated instructors to upskill your teams.

Azure Data Engineering serves as the backbone for any organization seeking to harness the full potential of their data within Microsoft's Azure cloud ecosystem. Azure services, such as Azure Data Factory, Azure Data Lake Storage, Azure Databricks, and Azure SQL Data Warehouse, enable companies to ingest, process, and visualize data more efficiently than ever before.

By enrolling in the Azure Data Engineer instructor-led training course, organizations can fast-track their digital transformation journey by empowering the workforce to build scalable and secure data solutions in Azure. Our virtual / onsite Azure Data Engineer course emphasizes the significance of understanding data governance, security, and compliance within the Azure environment. With a mix of theoretical instruction and hands-on exercises, it aims to produce well-rounded professionals who can excel in data engineering in Azure.

Azure Data Engineering Training for Employees: Key Learning Outcomes

Develop essential skills from industry-recognized Azure Data Engineering training providers. The course includes the following key learning outcomes:

  • Create robust Data Lake solutions
  • Analyze Azure Data Factory pipelines
  • Evaluate data security measures in Azure
  • Implement Azure Databricks for data analytics
  • Synthesize data streams using Azure Stream Analytics

Key Benefits of the Training

  • Evaluate the cost-effectiveness and scalability of Azure services
  • Synthesize various data sources into a unified data pipeline through Azure Data Factory
  • Implement machine learning algorithms and models using Azure Machine Learning service
  • Analyze complex data sets using Azure's analytics tools such as Azure Databricks and Power BI
  • Create robust data lakes and storage solutions using Azure Data Lake Storage and Azure Blob Storage
  • Demonstrate the integration of real-time analytics into business operations using Azure Stream Analytics
  • Apply best practices in data security and compliance by using Azure’s built-in features, such as Azure Key Vault and Azure Active Directory

Azure Data Engineering Training Topics and Outline

This Azure Data Engineering Training curriculum is meticulously designed by industry experts according to the current industry requirements and standards. The program provides an interactive learning experience that focuses on the dynamic demands of the field, ensuring relevance and applicability.

  1. Define cloud computing
    • The evolution of cloud computing
    • Key characteristics of cloud computing
    • Service and deployment models in cloud computing
  2. Services offered by Microsoft Azure
    • Compute services
    • Storage services
    • Database services
    • Big data and analytics
  3. Benefits of cloud computing
    • Cost efficiency
    • Scalability and flexibility
    • Disaster recovery and business continuity
  4. Different kinds of cloud deployments
    • Public cloud
    • Private cloud
    • Hybrid cloud
  5. Different kinds of cloud services
    • Infrastructure as a Service (IaaS)
    • Platform as a Service (PaaS)
    • Software as a Service (SaaS)
  6. Differences between AWS and Microsoft Azure
    • Market share and growth
    • Service comparison
    • Pricing models
  7. Create Azure account
    • Account setup and configuration
    • Subscription management
  8. Azure services & architecture
    • Core architectural components
    • Design and compliance
  9. Create resource groups and resources in the Microsoft Azure
    • Resource group management
    • Resource deployment
  10. Create virtual machine
    • VM configuration
    • VM management
  11. Azure classic deployment vs. Azure resource manager
    • Deployment models comparison
    • Migration strategies
  1. Blob storage
    • Types of blobs
    • Lifecycle management
  2. Queues and files
    • Message queuing
    • File shares and sync
  3. Security in storage account
    • Encryption and key management
    • Security best practices
  4. Tables
    • Design and performance
    • Table API
  5. Share access signatures
    • Creating and managing SAS
    • SAS security considerations
  6. Access keys
    • Managing access keys
    • Rotating access keys
  1. What is Azure SQL
    • Features and capabilities
    • Azure SQL vs. on-premises SQL server
  2. Different kinds of deployments in Azure
    • Single database
    • Elastic pool
    • Managed instance
  3. Azure SQL managed instance
    • Managed instance features
    • Migration to managed instance
  4. Azure SQL in virtual machine
    • SQL server on Azure VMs
    • Best practices for running SQL in VM
  5. Creating Azure SQL server
    • Server setup
    • Configuration options
  6. Creating database in Azure SQL server
    • Database deployment
    • Database configuration
  7. Elastic pool in the Azure SQL database
    • Elastic pool benefits
    • Elastic pool pricing and performance
  8. Different types of pricing tiers in the Azure SQL
    • Pricing models
    • Scaling and performance tiers
  9. Querying Azure SQL server from the on-site SSMS and cloud
    • Connectivity and security
    • Query performance tuning
  10. Loading data from on-site to the cloud SQL server
    • Data migration strategies
    • Tools and services for data transfer
  1. Compare SQL database and Azure data warehouse
    • Feature comparison
    • Use case scenarios
  2. Creating Azure data warehouse
    • Provisioning data warehouse
    • Initial configuration
  3. Polybase
    • Polybase configuration
    • Data loading with polybase
  1. Differentiate Azure data factory and SSIS
    • ETL process comparison
    • Use cases and scenarios
  2. Pipelines
    • Building and managing pipelines
    • Pipeline activities
  3. Copy data
    • Data movement activities
    • Performance tuning
  4. Monitoring and debugging pipelines
    • Monitoring tools
    • Debugging techniques
  5. Incremental loading in the Azure data factory
    • Incremental load patterns
    • Change data capture
  1. Getting started with the logic apps
    • Logic apps overview
    • Workflow design
  2. Sending mail logic app in Azure data factory
    • Email trigger configuration
    • Email action setup
  1. Tabular model of Azure analysis services
    • Tabular model basics
    • Data modeling
  2. Relationships
    • Designing relationships
    • Performance implications
  3. Deployment and migration of tabular project
    • Deployment strategies
    • Migration considerations
  1. Data lake gen 1 vs gen 2
    • Feature comparison
    • Migration path
  2. Azure data lake analytics
    • Analytics job design
    • Job scheduling and management
  1. Different types of cluster in Azure data bricks
    • Cluster configuration
    • Cluster optimization
  2. Working with Scala and Python
    • Language comparison
    • ETL process with Scala and Python
  1. Different types of consistency levels in Cosmos DB
    • Consistency level overview
    • Choosing the right level
  2. Level security of Cosmos DB
    • Security features
    • Best practices
  1. Azure active directory
    • Identity management
    • Authentication and authorization
  2. Role-based access control
    • Role definition
    • Role assignment

This Corporate Training for Azure Data Engineering is ideal for:

What Sets Us Apart?

Azure Data Engineering Corporate Training Prices

Elevate your team's Azure Data Engineering skills with our Azure Data Engineering corporate training course. Choose from transparent pricing options tailored to your needs. Whether you have a training requirement for a small group or for large groups, our training solutions have you covered.

Small Group
Large Groups

Request for a quote to know about our Azure Data Engineering corporate training cost and plan the training initiative for your teams. Our cost-effective Azure Data Engineering training pricing ensures you receive the highest value on your investment.

Request for a Quote

Our customized corporate training packages offer various benefits. Maximize your organization's training budget and save big on your Azure Data Engineering training by choosing one of our training packages. This option is best suited for organizations with multiple training requirements. Our training packages are a cost-effective way to scale up your workforce skill transformation efforts..

Starter Package

125 licenses

64 hours of training (includes VILT/In-person On-site)

Tailored for SMBs

Most Popular
Growth Package

350 licenses

160 hours of training (includes VILT/In-person On-site)

Ideal for growing SMBs

Enterprise Package

900 licenses

400 hours of training (includes VILT/In-person On-site)

Designed for large corporations

Custom Package

Unlimited licenses

Unlimited duration

Designed for large corporations

View Corporate Training Packages

This Corporate Training for Azure Data Engineering is ideal for:

The training course is designed for IT managers and CTOs, data engineers, software developers, DevOps teams, business intelligence analysts, database administrators, compliance officers, data architects, analytics teams, and security teams.

Prerequisites for Azure Data Engineering Training

The Azure Data Engineer training course requires a basic understanding of ETL, SQL Server, and Data Analytics.

Assess the Training Effectiveness

Bringing you the Best Azure Data Engineering Trainers in the Industry

The instructor-led Azure Data Engineering Training training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Azure Data Engineering practices.

Sanjay
Sanjay
Bhopal, India
Trainer since
June, 2019
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View Sanjay 's Profile

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