Microsoft Fabric Analytics Engineering Training Course

 Microsoft Fabric Analytics Engineering Training Course 

Introduction 

Microsoft Fabric Analytics Engineering Training Course is designed to equip professionals with practical skills in modern data analytics, enterprise data management, and cloud-based business intelligence. The course provides comprehensive knowledge of Microsoft Fabric, an integrated analytics platform that combines data engineering, data warehousing, real-time intelligence, data science, and business intelligence within a unified environment. Participants will explore Microsoft Fabric architecture, OneLake, Lakehouse, Data Warehouse, Microsoft Fabric notebooks, Data Factory, and Power BI to develop scalable, secure, and high-performance analytics solutions. Emphasis is placed on data integration, ETL and ELT pipelines, data transformation, semantic modelling, and enterprise data governance. 

The training further develops advanced capabilities in analytics engineering, dimensional modelling, SQL, Python, DAX, data orchestration, and automated reporting. Participants will gain practical experience designing end-to-end analytics workflows, implementing medallion architecture, optimising data pipelines, and delivering actionable business insights. Through hands-on exercises and global industry case studies, including retail analytics, financial services, healthcare data management, and supply chain intelligence, learners will understand how organisations leverage Microsoft Fabric to improve operational efficiency, enable data-driven decision-making, and accelerate digital transformation. 

Course Objectives 

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

1. Understand Microsoft Fabric architecture and unified analytics capabilities.
2. Implement OneLake storage and enterprise data management.
3. Design scalable Lakehouse and Data Warehouse solutions.
4. Develop advanced ETL and ELT data pipelines.
5. Apply SQL and Python for analytics engineering.
6. Implement medallion architecture and data transformation.
7. Develop reusable Microsoft Fabric notebooks.
8. Build enterprise-grade semantic models.
9. Apply DAX for advanced analytical calculations.
10. Integrate Power BI for interactive business intelligence.
11. Implement data governance, security, and compliance.
12. Optimise analytics workloads and pipeline performance.
13. Automate data workflows and enterprise reporting.

Organizational Benefits
 

1. Improved enterprise data integration and accessibility.
2. Enhanced data-driven strategic decision-making.
3. Reduced data duplication through OneLake.
4. Increased analytics productivity and automation.
5. Improved business intelligence and reporting.
6. Optimised cloud data infrastructure costs.
7. Strengthened data governance and security.
8. Faster delivery of actionable business insights.
9. Improved cross-departmental data collaboration.
10. Enhanced digital transformation and innovation.

Target Audiences
 

1. Data engineers and analytics engineers.
2. Business intelligence professionals.
3. Data analysts and business analysts.
4. Database administrators and SQL developers.
5. Microsoft Azure and cloud professionals.
6. Power BI developers and consultants.
7. Enterprise data architects.
8. IT managers and digital transformation specialists.

Course Duration: 5 days

Course Modules

Module 1: Microsoft Fabric Architecture and Core Concepts
 

• Microsoft Fabric ecosystem and unified analytics architecture.
• Fabric workloads, capacities, and workspace management.
• OneLake architecture and data storage.
• Integration with Microsoft Azure and Power BI.
• Enterprise analytics architecture and deployment.
• Case study: Enterprise analytics integration at Microsoft.

Module 2: OneLake and Lakehouse Engineering
 

• OneLake storage architecture and data organisation.
• Lakehouse development and Delta Lake fundamentals.
• Medallion architecture: Bronze, Silver, and Gold layers.
• Data ingestion and transformation strategies.
• Schema management and data quality validation.
• Case study: Retail data consolidation using Lakehouse architecture.

Module 3: Data Engineering with Microsoft Fabric
 

• Data Factory pipelines and dataflows.
• ETL and ELT pipeline development.
• Data ingestion from multiple enterprise sources.
• Pipeline scheduling and orchestration.
• Incremental loading and error handling.
• Case study: Global supply chain data integration.

Module 4: SQL, Python and Notebook Engineering
 

• SQL querying and advanced data manipulation.
• Python programming for analytics engineering.
• PySpark and distributed data processing.
• Notebook development and execution.
• Data cleansing and transformation automation.
• Case study: Financial transaction analytics using PySpark.

Module 5: Data Warehousing and Dimensional Modelling
 

• Fabric Data Warehouse architecture.
• Star and snowflake schema development.
• Fact tables and dimension tables.
• T-SQL development and query optimisation.
• Data modelling and warehouse performance.
• Case study: Banking enterprise data warehouse implementation.

Module 6: Semantic Modelling and Power BI Analytics
 

• Semantic model development and relationships.
• DAX measures and calculated columns.
• Data modelling and analytical performance.
• Power BI dashboards and interactive visualisation.
• Row-level security and reporting governance.
• Case study: Healthcare performance dashboards and analytics.

Module 7: Real-Time Analytics and Data Governance
 

• Real-Time Intelligence and eventstream processing.
• Eventhouse and real-time data analytics.
• Data lineage and governance management.
• Workspace security and access control.
• Data monitoring, compliance, and quality assurance.
• Case study: Real-time financial fraud monitoring.

Module 8: Analytics Optimisation and Enterprise Deployment
 

• Microsoft Fabric workload optimisation.
• Capacity management and performance monitoring.
• CI/CD and analytics deployment strategies.
• Pipeline automation and operational monitoring.
• Enterprise analytics solution documentation.
• Case study: Global enterprise analytics modernisation.

Training Methodology
 

• Instructor-led presentations and interactive discussions.
• Practical Microsoft Fabric laboratory exercises.
• Hands-on data engineering and analytics projects.
• Real-world enterprise case studies and demonstrations.
• Group assignments and collaborative problem-solving.
• Practical assessments and knowledge evaluation.
• Capstone project involving end-to-end analytics engineering.
• Expert guidance on enterprise implementation strategies.

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.