Microsoft Fabric Data Engineer Course in Saudi Arabia

Upcoming sessions

Curriculum

1

Understand Microsoft Fabric architecture

2

Configure workspaces and capacities

3

Manage compute and resources

4

Implement access and permissions

5

Monitor Fabric usage and performance

1

Design and implement data ingestion pipelines

2

Use Data Factory in Fabric

3

Create Dataflows Gen2

4

Transform data using Power Query

5

Schedule and orchestrate data pipelines

1

Create and manage Lakehouse in Fabric

2

Work with Delta tables

3

Organize data in OneLake

4

Use notebooks for data processing

5

Optimize Lakehouse performance

1

Design and implement Fabric Data Warehouse

2

Create tables, views, and schemas

3

Load and transform data

4

Optimize queries and performance

1

Implement real-time data streams

2

Use Eventstreams in Fabric

3

Process streaming data

4

Design real-time analytics solutions

5

Monitor streaming pipelines

1

Orchestrate workflows using pipelines

2

Monitor pipeline execution

3

Implement logging and alerting

4

Troubleshoot data workflows

5

Optimize pipeline performance

1

End-to-end data solution design

2

Requirement analysis (data, latency, performance)

3

Trade-off analysis (cost vs performance vs scalability)

4

Designing integrated data platforms

5

SLA-driven architecture

1

Ingest transactional data from multiple banking systems

2

Implement real-time streaming for fraud detection

3

Build Lakehouse for historical financial data

4

Create dashboards for risk monitoring and reporting

5

Generate fraud detection pipeline logic

6

Suggest real-time architecture for transaction monitoring

7

Analyze financial data patterns and anomalies

8

Draft executive summaries for risk insights

9

Ingest patient data from EHR systems and IoT devices

10

Build a Lakehouse for clinical and operational data

11

Implement real-time alerts for critical patient conditions

12

Ensure data governance and compliance considerations

13

Design healthcare data pipelines

14

Generate real-time alert logic

15

Explain compliance considerations (HIPAA-style scenarios)

16

Summarize patient insights for clinical decision-making

17

Ingest IoT sensor data from machines

18

Implement real-time processing for anomaly detection

19

Build predictive maintenance models using historical data

20

Monitor production efficiency and downtime

21

Generate predictive maintenance workflows

22

Analyze machine data trends and anomalies

23

Suggest optimization strategies for production pipelines

24

Create maintenance reporting summaries

25

Ingest sales, customer, and inventory data

26

Build a unified Lakehouse for customer analytics

27

Implement real-time sales tracking and recommendations

28

Create dashboards for demand forecasting and inventory planning

29

Generate customer segmentation logic

30

Analyze sales trends and demand patterns

31

Suggest real-time recommendation strategies

32

Draft business insights for marketing and operations teams

33

Design a scalable Fabric architecture supporting multiple domains

34

Define data ingestion, storage, and processing strategies

35

Address performance, cost, governance, and scalability trade-offs

36

Present an end-to-end enterprise data strategy

37

Generate architecture blueprints across domains

38

Compare multiple design approaches (cost vs performance)

39

Assist in cross-domain data modeling strategies

40

Prepare executive-level presentations and justifications

Meet your Trainer

Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

Our Trainers

Learning Outcomes

After completing this course, professionals will be able to:

1

Design workspace configurations, capacity plans, and role-based access controls in Microsoft Fabric

2

Implement ingestion and transformation pipelines using Data Factory, Dataflows Gen2, and Power Query

3

Build Lakehouse solutions with Delta tables, OneLake storage, and notebook-based data processing

4

Develop Data Warehouse schemas, views, and optimised queries for enterprise analytics workloads

5

Orchestrate Eventstreams and real-time pipelines with logging, alerting, and performance monitoring

6

Translate business requirements into SLA-driven Fabric architectures through capstone solution design

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KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

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Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

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Prerequisites

There are no formal prerequisites for this training program. However it is recommended to have:

A prior knowledge of ETL/data integration basics, orchestration concepts, and at least one of SQL, PySpark, or KQL

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Frequently asked questions

The Microsoft Fabric Data Engineer Course in Saudi Arabia covers Microsoft Fabric environment management through architecture, workspaces, capacities, compute, resource management, and access controls. It also includes usage monitoring and performance tracking, which are essential for managing enterprise data platforms.

Our course adds practical context through a module case study on workspace and capacity strategy for a multi-team enterprise analytics platform. Scenario-based mock tests and Copilot-supported tasks help participants understand configuration decisions, role-based access, and monitoring considerations.

The Microsoft Fabric Course in the KSA includes several design-focused areas across the Microsoft Fabric ecosystem. These include data ingestion pipeline design, Lakehouse architecture, Data Warehouse design, and real-time analytics solution design. It gives participants a structured view of how modern data platforms are planned and connected.

It also covers monitoring and alerting system design, streaming architecture, and end-to-end platform planning through the capstone module. That final module introduces requirement analysis, trade-off analysis, integrated data platform design, and SLA-driven architecture, which are central to enterprise-scale solution planning.

This course is relevant for teams in Riyadh working across shared analytics environments because it covers the control areas needed to manage a common Microsoft Fabric setup. These include workspaces, capacities, compute, resource management, permissions, and performance monitoring for enterprise-scale data operations.

It also adds practical context through a module case study on a multi-team enterprise analytics platform. That helps Riyadh-based teams understand how shared environments support coordinated access, capacity planning, workflow visibility, and more consistent decision-making across larger analytics functions.

The capstone module brings together the main Microsoft Fabric learning areas into one applied design exercise, helping participants connect requirements, architecture choices, performance needs, and scalability considerations clearly.

It includes the following:

End-to-end data engineering design within Microsoft Fabric
Requirement analysis for business, data, and latency needs
Trade-off analysis across performance, cost, and scalability factors
Integrated platform design covering connected Fabric workloads
SLA-driven architecture for enterprise data solution planning
Case-study-based assessment aligned with the DP-700 learning context

This course presents these Microsoft Fabric workloads as connected parts of one data engineering environment. It helps participants understand how ingestion, storage, streaming, and monitoring support enterprise analytics delivery.

Here is how this course connects Lakehouse, Data Warehouse, and real-time workloads:

Data ingestion and transformation pipelines prepare information for downstream Fabric workloads
Lakehouse implementation uses OneLake, Delta tables, and notebooks for analytics-ready data handling
Data Warehouse coverage includes tables, views, schemas, and structured loading for reporting needs
Real-time intelligence introduces Eventstreams, streaming data processing, and live analytics design
Workflow orchestration and monitoring show how these workloads operate within one connected platform
Capstone solution design brings Lakehouse, Data Warehouse, and real-time workloads into one end-to-end architecture

In this course, Copilot supports practical Microsoft Fabric learning by helping participants interpret architecture choices, streamline technical tasks, refine logic, and document decisions more effectively across data engineering workflows.

This is how Copilot is applied in this course:

Architecture explanation for Microsoft Fabric environment and workspace decisions
ETL design support for ingestion pipelines and transformation planning
Power Query assistance for shaping data and automating process steps
Notebook scripting support for technical implementation and logic development
SQL optimisation guidance for query improvement and schema-related tasks
Streaming logic support for real-time intelligence and event-driven workflows
Troubleshooting analysis for monitoring issues and workflow performance review
Design documentation support for architecture comparison and solution planning

Learners Point stands out for this training in Riyadh because the approved course structure emphasises practical Microsoft Fabric application, scenario-led assessment, and enterprise-focused design exposure.

Some of the reasons are:

Structured Microsoft Fabric coverage across connected workloads
Scenario-based mock tests linked to the DP-700 context
Case-study-led learning for enterprise data decisions
Copilot-supported tasks across design and troubleshooting
Industry simulations across multiple enterprise scenarios
Capstone-based planning for end-to-end architecture design

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