DP-600T00: Microsoft Fabric Analytics Engineer Training & Certification Course
Build advanced analytics solutions using Microsoft Fabric, including lakehouses, warehouses, semantic models, SQL, DAX and KQL. Develop the skills required to design, optimize, secure and manage enterprise-scale analytics solutions and prepare for the DP-600: Implementing Analytics Solutions Using Microsoft Fabric certification exam.
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32 Hours (4 Days)
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Live Online / Classroom
Course Overview
The DP-600T00: Microsoft Fabric Analytics Engineer course by Microsoft is designed for data professionals preparing for the Exam DP-600: Implementing Analytics Solutions Using Microsoft Fabric, leading to the Microsoft Certified: Fabric Analytics Engineer Associate credential. This advanced training targets roles such as Data Analyst, Analytics Engineer, and Business Intelligence Developer, equipping them with skills to design and manage enterprise-scale analytics solutions. With Microsoft Fabric being adopted by over 25,000 organizations globally as of 2026, including Fortune 500 companies standardizing on Microsoft’s unified analytics platform, demand for certified professionals is rapidly increasing. The course is ideal for those with prior experience in SQL, DAX, and Power BI who aim to master modern data modeling and governance in cloud-scale environments.
Learners engage with core Microsoft Fabric components including lakehouses, warehouses, eventhouses, dataflows, notebooks, and T-SQL within the Azure-based Fabric portal. The hands-on labs, conducted directly in the Microsoft Fabric portal, guide students through real-world scenarios such as implementing a star schema in a lakehouse, transforming raw data using Spark notebooks, and building enterprise-grade semantic models with Power BI. A key project involves creating a secure, governed analytics solution that integrates data from multiple sources using OneLake, then configuring Direct Lake connectivity and implementing row-level security. Students also perform impact analysis across dependencies and deploy models using XMLA endpoints, simulating enterprise deployment workflows.
This course prepares candidates for the DP-600 certification, recognized by employers like Accenture, Deloitte, and Microsoft as a benchmark for analytics engineering expertise in Fabric. Certified professionals report average salary increases of 20% and median base salaries exceeding $115,000 in North America. Optiv Solutions enhances this official Microsoft curriculum with Guaranteed-to-Run scheduling, 1-on-1 instructor support, and access to live lab environments, ensuring mastery of complex topics like incremental refresh, DAX optimization, and workspace-level governance. Upon completion, learners are positioned to lead analytics modernization initiatives, driving data democratization and AI readiness across global enterprises.
Learners engage with core Microsoft Fabric components including lakehouses, warehouses, eventhouses, dataflows, notebooks, and T-SQL within the Azure-based Fabric portal. The hands-on labs, conducted directly in the Microsoft Fabric portal, guide students through real-world scenarios such as implementing a star schema in a lakehouse, transforming raw data using Spark notebooks, and building enterprise-grade semantic models with Power BI. A key project involves creating a secure, governed analytics solution that integrates data from multiple sources using OneLake, then configuring Direct Lake connectivity and implementing row-level security. Students also perform impact analysis across dependencies and deploy models using XMLA endpoints, simulating enterprise deployment workflows.
This course prepares candidates for the DP-600 certification, recognized by employers like Accenture, Deloitte, and Microsoft as a benchmark for analytics engineering expertise in Fabric. Certified professionals report average salary increases of 20% and median base salaries exceeding $115,000 in North America. Optiv Solutions enhances this official Microsoft curriculum with Guaranteed-to-Run scheduling, 1-on-1 instructor support, and access to live lab environments, ensuring mastery of complex topics like incremental refresh, DAX optimization, and workspace-level governance. Upon completion, learners are positioned to lead analytics modernization initiatives, driving data democratization and AI readiness across global enterprises.
Skills You’ll Develop
✦ Microsoft Fabric
✦ Microsoft OneLake
✦ Lakehouse Architecture
✦ Data Warehousing
✦ Data Integration
✦ Data Ingestion
✦ Data Transformation
✦ Data Modeling
✦ Dimensional Modeling
✦ Star Schema Design
✦ Semantic Modeling
✦ Power BI Semantic Models
✦ Direct Lake
✦ Composite Models
✦ DAX
✦ SQL
✦ T-SQL
✦ Kusto Query Language
✦ KQL
✦ Dataflows Gen2
✦ Data Pipelines
✦ Fabric Notebooks
✦ Data Quality
✦ Data Cleansing
✦ Data Governance
✦ Data Security
✦ Row-Level Security
✦ Column-Level Security
✦ Object-Level Security
✦ Sensitivity Labels
✦ Workspace Management
✦ Deployment Pipelines
✦ Git Version Control
✦ XMLA Endpoint
✦ Incremental Refresh
✦ Query Optimization
✦ DAX Optimization
✦ Enterprise Analytics
✦ Analytics Lifecycle Management
✦ Performance Tuning
✦ Data Visualization
✦ Business Intelligence
Who Should Attend
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WHO SHOULD ATTEND (TARGET AUDIENCE)
• Data Analysts
• Analytics Engineers
• Business Intelligence Developers
• Power BI Professionals
• Data Engineers
• BI Engineers
• Data Architects
• Analytics Architects
• Database Professionals
• Cloud Data Professionals
• Technical Consultants
• Analytics Engineers
• Business Intelligence Developers
• Power BI Professionals
• Data Engineers
• BI Engineers
• Data Architects
• Analytics Architects
• Database Professionals
• Cloud Data Professionals
• Technical Consultants
Pre-requisites
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RECOMMENDED KNOWLEDGE BEFORE TAKING THIS COURSE
- ✓ Microsoft Certified: Data Analyst Associate (PL-300) or equivalent Power BI expertise
- ✓ Experience converting business needs into analytical measures using SQL or Data Analysis Expressions (DAX)
- ✓ Practical experience creating semantic models and reports in Power BI
- ✓ Knowledge of enterprise data modeling, transformation, and deployment workflows
- ✓ Proficiency with Kusto Query Language (KQL)
- ✓ Fundamental understanding of dataflow orchestration and notebook-based data transformation within cloud analytics platforms
Certification Exam Details
Everything you need to know about the certification exam
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Exam Details
EXAM
CODE
DP-600
EXAM
NAME
Microsoft Fabric Analytics Engineer
FORMAT
Multiple Choice Questions (MCQs) and Scenario-Based Questions
QUESTIONS
40-60 questions
DURATION
100 minutes
PASSING
SCORE
700 (out of 1000)
Upcoming Batch Schedule
Enroll in upcoming batches and start your learning journey
📅
No Public Batch Available. Pick Your Dates
4 Hours / 8 Hours
• Weekdays / Weekends
Curriculum & Course Syllabus
Module 1: Explore End-to-End Analytics with Microsoft Fabric
- Introduction to Microsoft Fabric
- Microsoft Fabric architecture
- Fabric workloads
- End-to-end analytics
- Fabric workspaces
- Fabric items
- OneLake overview
- Data analytics lifecycle
- Analytics personas and roles
- Microsoft Fabric capacity concepts
- Fabric administration fundamentals
- Choosing the right Fabric workload
Module 2: Work with Microsoft Fabric Data Stores
- Microsoft OneLake
- OneLake architecture
- OneLake data organization
- Lakehouse fundamentals
- Lakehouse architecture
- Lakehouse Explorer
- Tables and files
- Delta Lake
- Shortcuts
- OneLake shortcuts
- Data discovery
- Microsoft Fabric Warehouse
- Warehouse architecture
- SQL analytics endpoint
- Eventhouse fundamentals
- Choosing between Lakehouse, Warehouse and Eventhouse
Module 3: Ingest Data into Microsoft Fabric
- Data ingestion concepts
- Connecting to data sources
- Data connectors
- Data ingestion strategies
- Data pipelines
- Pipeline activities
- Dataflow Gen2
- Copy activities
- Data movement
- Data integration
- Incremental data ingestion
- Batch ingestion
- Streaming considerations
- OneLake integration
- Real-Time hub
- OneLake catalog
- Choosing appropriate ingestion methods
Module 4: Transform and Enrich Data
- Data transformation fundamentals
- Power Query
- Dataflow Gen2 transformations
- Data cleansing
- Handling missing values
- Handling null values
- Removing duplicate records
- Data type conversion
- Filtering data
- Joining datasets
- Merging datasets
- Aggregating data
- Creating calculated columns
- Creating new tables
- Data enrichment
- Data transformation using SQL
- Views
- Functions
- Stored procedures
- Data transformation using notebooks
Module 5: Design Dimensional Data Models
- Data modeling fundamentals
- Dimensional modeling
- Fact tables
- Dimension tables
- Star schemas
- Snowflake schemas
- Relationships
- Primary and foreign keys
- Cardinality
- Denormalization
- Data aggregation
- Many-to-many relationships
- Bridge tables
- Analytical model design
- Choosing appropriate model structures
Module 6: Query Data Using SQL
- SQL fundamentals for analytics
- SELECT statements
- Filtering data
- Sorting data
- Aggregating data
- GROUP BY
- HAVING
- JOIN operations
- Subqueries
- Common table expressions
- Window functions
- Analytical SQL
- Views
- Stored procedures
- Functions
- Query optimization
- T-SQL in Fabric Warehouse
Module 7: Query Data Using KQL
- Introduction to Kusto Query Language
- KQL syntax
- Tables and columns
- Filtering data
- Projection
- Sorting
- Aggregation
- Summarization
- Joining data
- Time-based analysis
- KQL operators
- KQL functions
- Eventhouse analytics
- Real-time data analysis
Module 8: Query and Analyze Data Using DAX
- DAX fundamentals
- Measures
- Calculated columns
- Calculated tables
- Filter context
- Row context
- Context transition
- CALCULATE
- DAX variables
- Iterators
- Table filtering
- Time intelligence
- Windowing functions
- Information functions
- Advanced DAX calculations
- DAX performance considerations
Module 9: Build and Manage Semantic Models
- Semantic model fundamentals
- Designing semantic models
- Star schema implementation
- Relationships
- Relationship filtering
- Many-to-many relationships
- Bridge tables
- Storage modes
- Import mode
- DirectQuery
- Direct Lake
- Composite models
- Large semantic models
- Semantic model properties
- Reusable semantic models
Module 10: Optimize Enterprise-Scale Semantic Models
- Semantic model optimization
- Query performance
- Report visual performance
- DAX performance optimization
- Model size optimization
- Direct Lake
- Direct Lake on OneLake
- Direct Lake on SQL analytics endpoint
- Direct Lake fallback behavior
- Refresh behavior
- Incremental refresh
- Large semantic model storage
- Performance monitoring
Module 11: Secure and Govern Analytics Solutions
- Microsoft Fabric security
- Workspace-level access
- Item-level access
- Row-level security
- Column-level security
- Object-level security
- File-level access
- Permissions management
- Sensitivity labels
- Data governance
- Data endorsement
- Trusted data assets
- Security best practices
Module 12: Manage the Analytics Development Lifecycle
- Analytics lifecycle
- Development environments
- Version control
- Git integration
- Workspace version control
- Power BI Desktop projects
- PBIP files
- Deployment pipelines
- Development-to-production deployment
- Deployment stages
- Impact analysis
- Dependency management
- XMLA endpoint
- Semantic model deployment
- Reusable analytics assets
- PBIT files
- PBIDS files
- Shared semantic models
Module 13: Monitor and Maintain Analytics Solutions
- Analytics solution monitoring
- Workspace monitoring
- Capacity considerations
- Query performance
- Semantic model monitoring
- Data refresh monitoring
- Troubleshooting failed refreshes
- Dependency analysis
- Performance optimization
- Data quality monitoring
- Analytics lifecycle maintenance
- Operational best practices
Module 14: AI-Ready Analytics Data
- Preparing data for AI workloads
- AI-ready analytics
- Preparing trusted data
- Semantic models for AI
- Data quality for AI
- Structured analytical data
- Microsoft Fabric and AI
- Supporting AI agents with analytical data
- Data accessibility and discoverability
Module 15: Practical Project – Enterprise Analytics Solution
- Business requirements analysis
- Source-system assessment
- Data ingestion
- Lakehouse implementation
- Warehouse implementation
- Data transformation
- Star schema development
- Semantic model creation
- DAX measures
- Direct Lake implementation
- Security configuration
- Data governance
- Deployment pipeline
- Performance optimization
- Analytics validation
- Business reporting
- End-to-end Fabric analytics architecture
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Frequently Asked Questions
Is the DP-600 certification exam included in the DP-600T00: Microsoft Fabric Analytics Engineer training, and what is the cost?
The DP-600 certification exam is not included in the DP-600T00: Microsoft Fabric Analytics Engineer course and requires separate purchase. The exam fee is $165 USD, varying by region. You can schedule your exam via Pearson VUE after completing this Microsoft training.
How long is lab access provided for the DP-600T00: Microsoft Fabric Analytics Engineer course, and what environment is used?
Lab access for the DP-600T00: Microsoft Fabric Analytics Engineer course lasts 30 days post-enrollment, using Microsoft-hosted cloud sandboxes. These hands-on labs enable you to master implementing analytics solutions within Microsoft Fabric using authentic, real-world data scenarios and tools.
What is the format, question count, time limit, and passing score for the DP-600 certification exam?
The DP-600 exam features 40–60 questions, including multiple-choice and case studies, with a 100-minute limit. A passing score of 700/1000 is required. This proctored exam evaluates your expertise in data preparation, semantic modeling, and analytics solution management within Microsoft Fabric.
How long is the Microsoft Certified: Fabric Analytics Engineer Associate certification valid, and what is the renewal process?
This certification is valid for 12 months and requires annual renewal. You can renew by passing a free online assessment on Microsoft Learn, which validates your ongoing skills in data security, Power BI assets, and semantic model optimization techniques.
Does Optiv provide post-training support such as mentor access or retake options for the DP-600T00: Microsoft Fabric Analytics Engineer course?
Optiv offers post-training support, including expert instructor access, a global learner community, and Certificate Insurance with a free second exam attempt. Flexi learners may also request additional live 4-hour interactive sessions to deepen their understanding of Microsoft Fabric.