Microsoft DP-700T00-A: Implement Data Engineering Solutions Using Microsoft Fabric Course
50-70-hour Microsoft Fabric Engineering program
Globally recognised DP-700 Data Engineer certification
Automated workflows using Copilot integration
7-modules, expert-Led simulations & mock tests
Flexible learning options with easy instalments
4.85/55289 EnrolledEnrolled Learners
4.85/55289 EnrolledEnrolled Learners
Overview
What our training includes:
- Get unified Microsoft Fabric coverage across ingestion, storage, and orchestration
- Explore integrated learning across Lakehouse, Data Warehouse, and Data Factory
- Gain platform skills using Delta tables, OneLake, notebooks, and pipelines
- Develop enterprise-focused capability in workspaces, capacities, compute, and permissions
- Strengthen real-time intelligence skills for streaming design and workflow monitoring
- Acquire practical exposure through case studies, mock tests, Copilot, and industry simulations
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.
Learning Outcomes
After completing this course, professionals will be able to:
1
Design Microsoft Fabric environments for scalable enterprise data operations
2
Implement data ingestion and transformation pipelines across Fabric workloads
3
Build Lakehouse solutions using OneLake, Delta tables, and notebooks
4
Develop Data Warehouse structures for analytics and reporting needs
5
Orchestrate streaming workflows with monitoring, logging, and alerting controls
6
Translate business requirements into scalable Microsoft Fabric solution designs
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.
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
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 is a practical training program that helps participants build data engineering solutions using Microsoft Fabric. It covers Fabric architecture, data ingestion, transformation, Lakehouse, Data Warehouse, real-time intelligence, orchestration, monitoring, and workflow optimisation through structured learning and applied practice.
It is ideal for participants working with data platforms, analytics workflows, BI reporting, or cloud-based data solutions. The course suits Data Engineers, BI Developers, Analytics Engineers, ETL professionals, and Data Architects seeking DP-700 exam preparation and stronger workplace capability.
Yes. Participants new to Microsoft Fabric can take this training if they are ready to work with basic data engineering concepts. This course begins with Fabric architecture, workspaces, capacities, access, and monitoring before moving into pipelines, Lakehouse, Data Warehouse, and real-time intelligence.
This structure helps participants build confidence step by step, not by rushing into advanced design too early. They practise ingestion, transformation, orchestration, troubleshooting, and optimisation through labs, case studies, mock tests, Copilot activities, and capstone work for DP-700 exam preparation.
Yes. The DP-700T00: Microsoft Fabric Data Engineer course supports DP-700 preparation because Microsoft lists it as a related learning path for the Fabric Data Engineer Associate credential. It covers core exam areas such as data ingestion, transformation, security, management, and monitoring.
It also aligns with the role expectations for a Fabric Data Engineer, including data loading patterns, data architectures, and orchestration processes. This makes the course useful for professionals seeking structured and platform-specific preparation before attempting the certification exam.
Our course combines core Microsoft Fabric tools with Copilot-supported tasks. This helps participants work across ingestion, storage, transformation, streaming, orchestration, troubleshooting, and solution design in a structured and enterprise-focused learning environment. This course includes the following tools and Copilot integration:
- Microsoft Fabric for unified data engineering workflows
- Lakehouse for modern analytics-focused data storage
- Data Warehouse for structured analytical design
- Data Factory for ingestion and pipeline workflows
- Dataflows Gen2 for transformation processes
- Power Query for data shaping and preparation
- OneLake for centralised data organisation
- Delta tables for Lakehouse data management
- Notebooks for technical implementation tasks
- Eventstreams for real-time data processing
- Pipelines for orchestration and workflow execution
- Copilot for architecture explanation and ETL design support
- Copilot for Power Query steps and notebook scripting
- Copilot for SQL optimisation and streaming logic support
- Copilot for troubleshooting analysis and design documentation
Yes. This DP-700 course includes real-time data engineering practice through the Real-Time Intelligence Solutions module and industry simulations. Participants work with Eventstreams, streaming pipelines, real-time analytics design, monitoring strategies, and live data scenarios that reflect practical business requirements.
The finance simulation is useful because it covers real-time transaction monitoring, anomaly detection, and risk reporting. Participants also practise monitoring streaming pipelines, troubleshooting failures, and improving workflow performance, giving them clearer confidence in applying Microsoft Fabric to time-sensitive analytics tasks and DP-700 exam preparation.
This course is relevant for both individual professionals and organisational teams because it combines expert-led Microsoft Fabric instruction with enterprise-grade project simulations. Here's why you should choose Learners Point for this course:
- Structured coverage of core Microsoft Fabric workloads
- Scenario-based mock tests aligned with DP-700 context
- Practical learning through case studies and simulations
- Copilot-supported tasks across design and troubleshooting activities
- Capstone-led exposure to end-to-end solution planning
- Relevant format for both upskilling and team capability building
Copilot is used as a practical support tool across the DP-700 Microsoft Fabric Course. Participants use it to explain Fabric concepts, generate ETL pipeline designs, support Power Query steps, create Lakehouse diagrams, optimise SQL queries, and simplify performance tuning ideas.
It also supports troubleshooting and architecture work. Participants use Copilot to analyse pipeline failures, design alerting systems, compare solution options, draft technical documentation, and prepare business-aligned justifications during capstone activities. This makes AI-assisted data engineering more practical and workplace relevant.
This Microsoft Fabric training uses industry simulations to help Participants apply data engineering, real-time analytics, and Fabric architecture decisions in practical business scenarios. It includes the following simulations:
- Finance simulation for real-time transaction monitoring, anomaly detection, and risk reporting
- Healthcare simulation for patient data integration, IoT monitoring, and critical alerts
- Manufacturing simulation for smart factory data, anomaly detection, and predictive maintenance
- Retail simulation for customer analytics, sales tracking, and demand forecasting
- Cross-domain enterprise simulation for scalable Fabric architecture across multiple business functions
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