Top Azure Data Engineering Certification Course
                     What is Azure Data Engineering?
Advantages and Disadvantages
What is Azure Data Engineering?
• Azure Data Engineering focuses on designing and managing scalable 
data systems on Microsoft Azure.
• Key features:
– Data ingestion, storage, processing, and visualization.
– Services like Azure Data Factory, Azure Data bricks, Azure Synapse 
Analytics, and Azure Storage.
• Purpose: Enabling businesses to derive insights and make data-driven 
decisions.
Core Components of Azure Data Engineering
 Data Integration: Azure Data Factory for ETL/ELT workflows.
 Data Storage: Azure Data Lake, Azure Blob Storage, SQL 
Database.
 Data Processing: Azure Data bricks, Azure Synapse 
Analytics.
 Data Visualization: Power BI integration for insights.
Advantages of Azure Data Engineering (Part 1)
 Scalability:
 Easily scale resources to handle big data workloads.
 Integration:
 Seamless integration with other Microsoft and third-party tools.
 Performance:
 High performance with distributed processing in Azure Data 
bricks and Synapse Analytics.
•Cost-Effectiveness:
•Cost-PEffaye-catis-vyeonue-sgso: pricing reduces infrastructure costs.
•Cost-PEffaye-catis-vyeonue-sgso: pricing reduces infrastructure costs.
Pay-as-you-go pricing reduces infrastructure costs.
Advantages of Azure Data Engineering (Part 2)
 Automation:
 Automate workflows with Azure Data Factory.
 Security and Compliance:
 Built-in data encryption, access controls, and compliance with 
standards like GDPR.
 Cost-Effectiveness:
 Pay-as-you-go pricing reduces infrastructure costs.
Disadvantages of Azure Data Engineering (Part 1)
 Learning Curve:
Requires expertise in Azure services and tools like Data bricks 
and Synapse.
 Complexity:
Managing distributed systems can be challenging.
 Dependency on Internet:
Continuous internet connectivity is required for cloud-based 
operations.
Disadvantages of Azure Data Engineering (Part 2)
 Cost Management:
Improper monitoring can lead to unexpected costs.
 Limited Offline Access:
Not ideal for environments with minimal internet access.
 Vendor Lock-In:
Migrating data and systems to another provider may be 
challenging.
Real-World Use Cases
 Retail: Customer behaviour analysis using Azure Data 
bricks.
 Healthcare: Real-time patient monitoring with Azure 
Synapse.
 Finance: Fraud detection through machine learning 
models in Azure AI.
 Entertainment: Content recommendation systems 
powered by Azure Data Factory.
Conclusion
 Summary:
 Azure Data Engineering enables scalable, secure, and 
integrated data solutions.
 Offers significant advantages but requires skilful management 
to avoid pitfalls.
 Call to Action:
 Explore Azure certifications for Data Engineering to enhance 
your skills.
CONTACT
Azure Data Engineering 
Address:- Flat no: 205, 2nd Floor,
Nilgiri Block, Aditya Enclave,
Ameer pet, Hyderabad-1 
Ph. No: +91-9989971070 
Visit: www.visualpath.in 
E-Mail: [email protected]
THANK YOU
Visit: www.visualpath.in