Microsoft Fabric Data Analytics with Lakehouse Reporting Training Course

Course overview

Many organisations have data spread across operational systems, spreadsheets, data warehouses and Power BI reports, making it difficult to produce trusted metrics quickly. Microsoft Fabric brings data engineering, lakehouse storage, SQL analytics and Power BI reporting into a single SaaS platform, but teams need practical design skills to avoid duplicated data, poorly governed workspaces and reports built on inconsistent calculations. This course equips participants to build an auditable reporting path from raw data ingestion through to governed business dashboards.

Participants work through Microsoft Fabric’s core analytics workloads, including OneLake, Lakehouses, Dataflows Gen2, Data Pipelines, notebooks, the SQL analytics endpoint, semantic models and Power BI reports. They learn how to structure data using bronze, silver and gold layers; load and transform data with Power Query and Spark; query Delta tables using SQL; create reusable DAX measures; and configure refresh, security and workspace permissions. The course also explains when to use a Lakehouse, Warehouse, Dataflow Gen2 or Power BI semantic model for a given reporting requirement.

Delivery combines instructor demonstrations with guided build exercises using a realistic sales and operations reporting scenario. Each participant creates a working Fabric analytics solution: an organised Lakehouse, ingestion and transformation process, curated reporting tables, a semantic model and an interactive Power BI report. The final day includes a design review and implementation plan, enabling participants to identify the data sources, governance decisions and delivery sequence needed to apply the approach in their own environment.

The course is suited to analysts, BI developers, data engineers and technical reporting leads who need to deliver governed self-service reporting on Microsoft Fabric. It is also valuable for managers responsible for establishing a practical Fabric operating model and improving confidence in organisational reporting.

Course objectives

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

• Design a Microsoft Fabric workspace and OneLake structure for a governed analytics use case
• Create a Lakehouse using bronze, silver and gold data layers with Delta tables
• Build Data Pipelines and Dataflows Gen2 to ingest and transform reporting data
• Use Fabric notebooks and PySpark to cleanse, join and enrich Lakehouse data
• Query curated Lakehouse tables through the SQL analytics endpoint using T-SQL
• Develop a Power BI semantic model with relationships, DAX measures and reusable business metrics
• Publish an interactive Power BI report with drill-through, filters and role-based data access
• Produce a Fabric solution design and implementation plan for a departmental reporting requirement

Benefits of attending

Target competencies

Who should attend

• Data Analysts — who need to turn multiple operational data sources into governed Power BI reporting
• Power BI Developers — who need to extend report development into Fabric Lakehouse and semantic model design
• Business Intelligence Developers — who build shared reporting datasets and need consistent transformation and deployment methods
• Data Engineers — who need to use Fabric Pipelines, notebooks and Delta tables for analytics delivery
• Reporting and Analytics Managers — who must establish trusted metrics, workspace controls and a practical Fabric delivery model
• Database and SQL Developers — who need to make curated data available through Fabric SQL analytics for business reporting

Requirements and prerequisites

Participants should be comfortable working with tabular data and understand basic concepts such as rows, columns, joins, data types, filters and business measures. Prior experience creating or consuming Power BI reports is helpful, and basic SQL familiarity will make the SQL analytics endpoint exercises easier. Participants should also be able to use Microsoft Excel and navigate a web-based Microsoft 365 environment. No prior Microsoft Fabric, Azure, PySpark, data engineering or DAX experience is required; these are introduced through guided exercises. Complete beginners should expect a technically practical week with structured support rather than an introductory course in general data literacy.

Training methodology

The course uses short instructor-led explanations followed by guided work in a Microsoft Fabric tenant. Participants progressively build a Lakehouse reporting solution from source files and operational extracts, using Dataflows Gen2, Pipelines, notebooks, SQL and Power BI. Instructor demonstrations focus on configuration decisions and common implementation mistakes; exercises require participants to make and test those decisions themselves. Small-group reviews compare data-layer and semantic-model designs. On the final day, participants present their solution and create an application plan for a live reporting requirement.

Course outline

Day 1: Microsoft Fabric foundations and analytics architecture

• Microsoft Fabric workloads and capacity concepts
• OneLake architecture and data item relationships
• Fabric tenant, domain and workspace organisation
• Lakehouse, Warehouse and Power BI semantic model selection
• Medallion architecture using bronze, silver and gold layers
• Delta Lake tables and managed table storage
• Workspace roles, item permissions and governance responsibilities

Workshop: Participants create a governed Fabric workspace and draft a Lakehouse architecture for a sales and operations reporting scenario.

Day 2: Data ingestion and Lakehouse transformation

• Creating Lakehouses and organising Files and Tables areas
• Dataflows Gen2 connectors and Power Query transformations
• Data Pipeline activities, parameters and execution dependencies
• Loading CSV, Excel and database extracts into OneLake
• Data quality checks for nulls, duplicates and invalid data types
• Bronze-to-silver transformation patterns
• Pipeline scheduling, monitoring and failure investigation

Workshop: Participants ingest source sales files through a Dataflow Gen2 and Pipeline, producing validated bronze and silver Delta tables.

Day 3: Notebook engineering and SQL analytics

• Fabric notebook interface and Spark session concepts
• PySpark DataFrame loading and schema inspection
• PySpark joins, aggregations and conditional transformations
• Writing curated gold tables in Delta format
• SQL analytics endpoint navigation and T-SQL querying
• Views and reporting-ready SQL query patterns
• Comparing notebook, Dataflow Gen2 and SQL transformation approaches

Workshop: Participants use a Fabric notebook to create a gold sales-performance table, then validate it with SQL analytics endpoint queries.

Day 4: Semantic models and Power BI Lakehouse reporting

• Connecting Power BI semantic models to Fabric Lakehouse tables
• Star schema design with fact and dimension tables
• Relationships, filter direction and model validation
• DAX measures for revenue, margin, variance and year-to-date analysis
• Calendar tables and time-intelligence calculation patterns
• Power BI report layout, drill-through and tooltip design
• Row-level security roles and semantic model access

Workshop: Participants build a semantic model and Power BI management report containing approved revenue, margin and variance measures.

Day 5: Governance, deployment and implementation planning

• Fabric lineage view and impact analysis
• Workspace lifecycle and development, test and production separation
• Deployment pipelines for Fabric items and Power BI content
• Refresh strategy, gateway considerations and operational monitoring
• Data ownership, certification and metric definition controls
• Performance tuning for Power BI models and Lakehouse queries
• Fabric solution documentation and implementation roadmaps

Workshop: Participants review their end-to-end solution, document governance controls and produce a phased Fabric implementation plan for their workplace.

Tools & standards covered

Microsoft Fabric, Microsoft OneLake, Power BI Desktop, Azure DevOps

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions