Microsoft Fabric Data Engineering Training Course

 Microsoft Fabric Data Engineering Training Course 

Introduction 

Microsoft Fabric Data Engineering Training Course is designed to equip participants with advanced technical skills for building, managing, and optimizing modern data engineering solutions using Microsoft Fabric. As organizations increasingly adopt cloud computing, artificial intelligence, big data analytics, and cloud-native data platforms, the ability to integrate, transform, store, and manage enterprise data has become essential. This practical training explores Microsoft Fabric architecture, OneLake, Lakehouse, Data Warehouse, Apache Spark, Delta Lake, Data Factory, real-time intelligence, and enterprise data integration. Participants gain hands-on experience in developing scalable data pipelines, implementing automated data transformations, managing distributed datasets, and building reliable data architectures that support business intelligence and advanced analytics. 

The course also examines modern data engineering practices, including data orchestration, data quality management, metadata governance, performance optimization, security, and enterprise data lifecycle management. Through practical exercises and international case studies, participants learn how to design efficient data ingestion frameworks, implement medallion architecture, integrate diverse data sources, and deploy production-ready data engineering workflows. The programme emphasizes real-world applications of Microsoft Fabric in financial services, healthcare, telecommunications, manufacturing, retail, and government institutions. By the end of the training, participants will be equipped to leverage Microsoft Fabric for enterprise data modernization, intelligent automation, cloud data management, and data-driven decision-making. 

Course Objectives 

By the end of this course, participants will be able to: 

1. Understand Microsoft Fabric architecture and unified analytics capabilities.
2. Design scalable enterprise data engineering solutions.
3. Implement OneLake storage and data management.
4. Develop Lakehouse architectures using Delta Lake.
5. Build automated data pipelines using Data Factory.
6. Apply Apache Spark for distributed data processing.
7. Implement advanced SQL-based data transformations.
8. Integrate structured and unstructured enterprise datasets.
9. Apply medallion architecture for data management.
10. Optimize data pipeline performance and scalability.
11. Implement data governance, security, and compliance.
12. Develop real-time data ingestion and processing workflows.
13. Apply artificial intelligence and cloud analytics technologies.

Organizational Benefits
 

1. Improved enterprise data integration and accessibility.
2. Reduced infrastructure and data management costs.
3. Enhanced business intelligence and reporting capabilities.
4. Faster data processing and analytical decision-making.
5. Improved data quality and operational efficiency.
6. Strengthened enterprise data security and governance.
7. Increased scalability of cloud data infrastructure.
8. Streamlined data engineering and automation workflows.
9. Better collaboration between analytics and IT teams.
10. Accelerated digital transformation and innovation.

Target Audiences
 

1. Data engineers and data architects.
2. Database administrators and SQL developers.
3. Business intelligence professionals.
4. Cloud computing and Azure specialists.
5. Data scientists and analytics professionals.
6. IT managers and technology consultants.
7. Software developers and enterprise architects.
8. Digital transformation and information systems professionals.

Course Duration: 5 days

Course Modules

Module 1: Introduction to Microsoft Fabric Architecture
 

• Microsoft Fabric ecosystem, architecture, and core components.
• Unified analytics, SaaS capabilities, and workspace management.
• Fabric capacity, licensing, and tenant administration.
• Integration with Microsoft Azure and Power BI.
• Enterprise data architecture and workload management.
• Case study: Microsoft's unified analytics approach in enterprise data modernization.

Module 2: OneLake Storage and Data Management
 

• OneLake architecture, storage organization, and shortcuts.
• Managing files, folders, and enterprise datasets.
• Understanding Delta Parquet and open data formats.
• Implementing data accessibility and sharing.
• OneLake security and access management.
• Case study: Global retail data consolidation using centralized cloud storage.

Module 3: Lakehouse Architecture and Delta Lake
 

• Lakehouse creation, configuration, and management.
• Implementing bronze, silver, and gold medallion layers.
• Delta tables, schema evolution, and transaction management.
• Managing batch ingestion and incremental loading.
• Data quality validation and transformation.
• Case study: Global banking data modernization using Lakehouse architecture.

Module 4: Data Engineering with Apache Spark
 

• Introduction to Spark notebooks and distributed computing.
• PySpark programming and DataFrame operations.
• Advanced data transformation and processing.
• Spark SQL, partitioning, and caching.
• Troubleshooting and optimizing Spark workloads.
• Case study: Large-scale telecommunications data processing using Apache Spark.

Module 5: Data Pipelines and Orchestration
 

• Developing pipelines using Microsoft Fabric Data Factory.
• Data ingestion from cloud and on-premises sources.
• Pipeline scheduling, monitoring, and automation.
• Implementing incremental data loading and CDC.
• Managing dependencies, parameters, and error handling.
• Case study: Global manufacturing supply-chain data integration.

Module 6: Data Warehousing and Advanced SQL
 

• Fabric Data Warehouse architecture and configuration.
• Developing SQL queries and stored procedures.
• Implementing dimensional modelling and star schemas.
• Managing warehouse performance and optimization.
• Integrating Lakehouse and warehouse environments.
• Case study: International financial institution implementing enterprise data warehousing.

Module 7: Real-Time Data Engineering and Analytics
 

• Real-Time Intelligence architecture and capabilities.
• Eventstreams, Eventhouse, and KQL databases.
• Streaming data ingestion and transformation.
• Real-time monitoring and analytical dashboards.
• Integrating event-driven data processing workflows.
• Case study: Global logistics company implementing real-time fleet monitoring.

Module 8: Data Governance, Security, and Deployment
 

• Implementing Microsoft Purview and data governance.
• Managing workspace permissions and access controls.
• Data lineage, auditing, and compliance management.
• CI/CD, Git integration, and deployment pipelines.
• Monitoring, troubleshooting, and production optimization.
• Case study: Healthcare organization implementing secure enterprise data governance.

Training Methodology
 

• Instructor-led presentations and interactive technical discussions.
• Practical Microsoft Fabric demonstrations and guided exercises.
• Hands-on Lakehouse, OneLake, and Data Factory development.
• Real-world enterprise projects and international case studies.
• Group assignments, technical problem-solving, and collaborative exercises.
• Practical assessments, knowledge checks, and final project presentations.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.
 
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
 
c. Course duration is flexible and the contents can be modified to fit any number of days.
 
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
 
e. One-year post-training support Consultation and Coaching provided after the course.
 f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.