Cloud Computing · PPL

Microsoft Azure Cloud Data Engineer Certification

Learn to design, build, secure, and optimize scalable data engineering solutions using Microsoft Azure's modern data platform and analytics services.

  • 4 DaysDuration
  • PPLAccredited
  • 3 LanguagesArabic · English · Hindi
  • ₹12,999.00 Per delegate

This course is accredited by PPL

This is for all ppl accredited courses
2M+ Delegates trained worldwide
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— The journey

Course Outline

What the programme covers, module by module.

Module 1: Azure Data Engineering Fundamentals

  • Microsoft Azure overview
  • Data engineering lifecycle
  • Azure architecture
  • Core data services
  • Solution design principles

Module 2: Azure Storage Services

  • Azure Blob Storage
  • Azure Data Lake Storage
  • Storage accounts
  • Data organization
  • Storage security

Module 3: Azure SQL and Databases

  • Azure SQL Database
  • Azure Cosmos DB
  • Azure Database for PostgreSQL
  • Database selection
  • Data management

Module 4: Data Ingestion

  • Azure Data Factory
  • Batch data ingestion
  • Real-time ingestion
  • Integration Runtime
  • Data movement strategies

Module 5: Data Transformation

  • ETL and ELT concepts
  • Mapping Data Flows
  • Data cleansing
  • Data enrichment
  • Transformation pipelines

Module 6: Azure Synapse Analytics

  • Synapse workspace
  • SQL pools
  • Spark pools
  • Data warehousing
  • Query optimization

Module 7: Azure Databricks

  • Apache Spark fundamentals
  • Notebook development
  • Cluster management
  • Data processing
  • Performance tuning

Module 8: Stream Processing

  • Azure Event Hubs
  • Azure Stream Analytics
  • Real-time analytics
  • Event processing
  • Streaming pipelines

Module 9: Workflow Orchestration

  • Azure Data Factory pipelines
  • Pipeline scheduling
  • Workflow automation
  • Dependency management
  • Monitoring workflows

Module 10: Data Warehousing

  • Data warehouse architecture
  • Data modeling
  • Partitioning
  • Performance optimization
  • Enterprise reporting

Module 11: Data Security

  • Microsoft Entra ID integration
  • Role-Based Access Control (RBAC)
  • Encryption
  • Azure Key Vault
  • Data protection

Module 12: Monitoring and Logging

  • Azure Monitor
  • Log Analytics
  • Metrics
  • Alerts
  • Operational dashboards

Module 13: Data Governance

  • Microsoft Purview
  • Data catalog
  • Data classification
  • Metadata management
  • Governance policies

Module 14: Machine Learning Integration

  • Azure Machine Learning overview
  • Data preparation
  • Feature engineering
  • Model integration
  • AI-enabled analytics

Module 15: Performance Optimization

  • Query tuning
  • Resource optimization
  • Storage optimization
  • Spark optimization
  • Cost-efficient processing

Module 16: Hybrid Data Solutions

  • Hybrid data architecture
  • Azure Arc overview
  • On-premises connectivity
  • Hybrid integration
  • Data synchronization

Module 17: Infrastructure Automation

  • Infrastructure as Code
  • Azure Resource Manager (ARM) Templates
  • Bicep overview
  • Deployment automation
  • Resource provisioning

Module 18: Backup and Disaster Recovery

  • Backup strategies
  • Geo-redundancy
  • Disaster recovery planning
  • Business continuity
  • Data resilience

Module 19: Cost Management

  • Azure pricing
  • Cost Management tools
  • Budget planning
  • Resource optimization
  • Financial governance

Module 20: Enterprise Data Architecture

  • Enterprise data platforms
  • Lakehouse architecture
  • Data mesh concepts
  • Scalable solutions
  • Best practices

Module 21: Cloud Migration

  • Migration planning
  • Database migration
  • Data validation
  • Migration tools
  • Modernization strategies

Module 22: Business Intelligence Integration

  • Microsoft Power BI integration
  • Data visualization
  • Dashboard development
  • Reporting architecture
  • Analytics workflows

Module 23: Operational Excellence

  • Reliability engineering
  • Operational monitoring
  • Incident management
  • Continuous improvement
  • Production readiness

Module 24: End-to-End Azure Data Engineering Solution

  • Data pipeline design
  • End-to-end implementation
  • Security integration
  • Performance optimization
  • Enterprise deployment
— 01.2 · Is it right for you?

Who it's for & what's included

Pick a delivery method to see exactly who it suits and everything you receive.

Who it's for

Classroom

Best for learners who want face-to-face tuition and to network with peers in person.

What's included

Everything you get

  • Live instructor on-site
  • Printed workbook & materials
  • Group exercises & case studies
Who it's for

Online Instructor-Led

Best for learners who want a live instructor and a fixed schedule, without the travel.

What's included

Everything you get

  • Live instructor via video call
  • Digital workbook & resources
  • Session recordings
Who it's for

Self-Paced

Best for self-motivated learners who need maximum flexibility around work and life.

What's included

Everything you get

  • On-demand video lessons
  • Interactive quizzes
  • 24/7 access on any device
— What you will master

Course Objectives

01

Design scalable data engineering solutions on Microsoft Azure

02

Build and manage batch and real-time data pipelines

03

Implement secure data storage and governance practices

04

Process and transform large datasets using Azure services

05

Optimize analytics workloads for performance and cost

06

Integrate machine learning and business intelligence solutions

07

Automate data engineering workflows and infrastructure

08

Design enterprise-grade Azure data platforms using best practices

— Questions answered

Frequently Asked Questions

Who should attend this course?
This course is ideal for data engineers, cloud engineers, analytics professionals, data architects, and experienced IT professionals working with Microsoft Azure.
Do I need prior Azure experience?
Yes. A working knowledge of cloud computing, SQL, and data processing concepts is recommended before attending this course.
Will the course include practical exercises?
Yes. Participants will build data pipelines, transform data, configure analytics services, implement governance, and optimize Azure data solutions through hands-on labs.
Which Microsoft Azure services are covered?
The course covers Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure SQL Database, Azure Blob Storage, Azure Data Lake Storage, Azure Monitor, Microsoft Purview, Azure Event Hubs, Azure Stream Analytics, and Azure Machine Learning.
— Trusted by learners

What our delegates say

★★★★★

"The structure, the practice exams, the instructor — all top tier. Passed first try."

AS
Aarti SharmaSenior Project Manager · TCS
★★★★★

"Best training I have attended. The content is exactly what modern projects need."

JD
James DonovanProgramme Director · Capgemini
★★★★★

"24/7 support actually means 24/7 — got help on my mock exam at 2am. Worth every dollar."

MO
Maya OkaforPMO Lead · Standard Bank

★ 4.8 / 5 from 12,000+ verified learner reviews on Trustpilot & Google.

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