Join us for a 5-day workshop designed to empower delegates in delivering an end-to-end #MicrosoftFabric Data Analytics solution. This workshop will follow best practices and be led by a Microsoft Certified Trainer (#MCT) with 30 years of experience in data management and analytics. This is an excellent opportunity to enhance your skills and knowledge in this vital area. Whilst understanding the extensive, features, limitations and work arounds when apply this technology to real world solutions.
Overview
This 5-day hands-on workshop teaches delegates how to design and build a production-ready Microsoft Fabric data platform from end to end.
Using a real-world data source (Xero as an example), delegates will implement industry-standard architecture patterns including Bronze, Silver, and Gold layers, incremental data pipelines, and a Power BI semantic model.
The workshop goes beyond theory—covering real-world design decisions, performance considerations, and common pitfalls encountered when delivering Fabric solutions in production environments.
This 5 day #MicrosoftFabric workshop will be delivered by an MCT with 30 years experience in data management and analytics.
The solution which delegates will create step by step will include …
1) Understanding and set up of the architecture within Fabric and Azure
2) Incremental load of data from source (e.g. Xero) into Bronze utilising PySpark
3) Incremental load of data from Bronze into Silver for cleansing and enrichment utilising T-SQL
4) Incremental load of data from Silver into Gold for reporting optimised data modelling via a star schema design utilising T-SQL
5) Incremental load of Gold layer to Semantic Layer where calculations require a user filter context utilising DAX
6) Delivery of Power BI Reporting.
The above will include AI, ML (Machine Learning) and MCP (Model Context Protocol)
How this differs from standard Fabric training
• Production-ready patterns (not demos)
• Incremental loading across all layers
• Real-world architecture decisions
• Performance + capacity considerations
• End-to-end implementation (not isolated labs)
Target Audience
· Data Engineers
· Analytics Engineers
· Data Architects
· BI Leads implementing Fabric
👉 NOT:
· Beginners
· General learners
Pre-requisites
The more knowledge a delegate has the better. It would be highly desirable if the delegates have …
1) Knowledge of the fundamentals of Azure as expressed within AZ 900.
2) Knowledge of Microsoft Fabric Analytics as expressed within DP 600.
3) Knowledge of Microsoft Fabric Engineering as expresed within DP 700.
Delegates are invited to give a summary of what they do and do not already know in relation to these optional pre-requisite training items so that delivery expectations of this training are managed. If not all the pre-requsites are met prior to the start of the course please still make an application and we will try and negociate a reasonable workaround.
Day 1 – Architecture & Setup
· Understanding and set up of the architecture within Fabric and Azure
· Fabric reference architecture
· An Environment per workspace with the setup of (Dev/UAT/Prod)
· Metadata tables (e.g. watermarks)
· Incremental load of data from source (e.g. Xero) into Bronze utilising PySpark
👉 Get this wrong and everything slows down later.
Day 2 – Source → Bronze
· Incremental load of data from source (e.g. Xero) into Bronze utilising PySpark
· Incremental loading strategies
· Watermarks & change tracking
· Error handling & monitoring
Day 3– Bronze → Silver
· Incremental load of data from Bronze into Silver for cleansing and enrichment utilising T-SQL
· Data cleansing & enrichment
· T-SQL vs PySpark trade-offs
Day 4 – Silver → Gold
· Incremental load of data from Silver into Gold for reporting optimised data modelling via a star schema design utilising T-SQL
· Star schema design
· Gold layer optimisation
· Performance considerations
Day 5 – Semantic Layer → Reporting
· Incremental load of Gold layer to Semantic Layer where calculations require a user filter context utilising DAX
· DAX modelling
· Power BI optimisation
· End-to-end solution walkthrough
· Delivery of Power BI Reporting.
The above will include AI, ML (Machine Learning) and MCP (Model Context Protocol)
· Using Fabric notebooks for ML
· Basic anomaly detection on financial data
· AI-assisted data exploration
Delivery Options
1) Deliver corporating to a class of delegates either in person or online.
2) Deliver to individuals online.
By the end of this workshop, delegates will be able to
1) Design a production-ready Fabric architecture
2) Implement incremental data pipelines at scale
3) Apply layered Lakehouse patterns (Bronze/Silver/Gold)
4) Build a star schema optimised for Power BI
5) Deliver a fully working reporting solution
6) Understand real-world trade-offs and performance considerations
Feedback
Please provide feedback on the above workshop. If you or your team are interested in attending this workshop please message me or post an entry to … https://www.dataplatformservices.com/contact/