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Power BI & Fabric TrainingTraining

Power BI & Microsoft Fabric Training

Our Power BI trainings cover the full path from raw data to a dashboard ready for a management presentation. Participants work with their own department’s data. The Microsoft Fabric trainings bring every analytics layer, from data integration to reporting, into one platform and work through these layers step by step on a single case selected from your organisation.

Power BI & Fabric Training

Trainings in This Category

Select a training to see its agenda, project cases and technical requirements.

Power BI Basic

Basic — Data Analysis and Reporting Fundamentals Training

2 DaysGet a Quote

01Training Overview

Duration
2 Days
Training Hours
09:30 – 16:30
Maximum Participants
10 Participants
Hands-on Ratio
80% Hands-on / 20% Theory
Certificate
Participants receive an IBA Consultancy Certificate of Participation at the end of the training.
Format
Online, On-site or Hybrid — set according to the organisation's preference.
Prerequisites
No software development knowledge is required. Basic Excel skills (formulas, working with tables) are sufficient.
Training Objective

This two-day training teaches participants to connect raw data in Power BI, build a basic data model, and prepare and share an interactive report. The programme covers connecting to a data source and basic Power Query transformations, simple data modelling, basic visualisation, and the basics of publishing/sharing in the Power BI Service through hands-on work.

This training is shorter and more introductory than IBA's PL-300 training (Microsoft Power BI Data Analysis and Visualisation, 4 days): it does not cover topics such as writing advanced measures with DAX, row-level security (RLS) and scheduled refresh. The organisation can later take its reporting to an advanced level with PL-300.

By the end of the training, participants can connect their own department's raw data, visualise it in a basic report and share it.

Technical Content

Power BI Fundamentals and Connecting Data

  • Introduction to Power BI Desktop and its interface
  • Connecting to a data source and basic Power Query transformations
  • Simple data modelling and relationships between tables

Visualisation and Sharing

  • Basic visualisation types and report design
  • Filters and slicers
  • Basics of publishing and sharing in the Power BI Service

02Exercises and Project Scenarios

Option A

Management Performance Dashboard

A basic dashboard tracking senior management metrics such as subscriber/member numbers, revenue and growth.

Option B

Sales and Stock Performance Dashboard

A basic dashboard tracking sales and stock levels by store/category.

Whichever case is chosen, the technical scope and outcomes of the training stay the same — the same data connection, modelling and visualisation topics are covered. The training is based on a single case chosen by the participant from their own department, and this case is built up step by step over the two days: on Day 1, the data source is connected and cleaned, and a basic data model is completed by creating relationships between tables; on Day 2, a basic set of visuals is created, filters/slicers are added and the report is published to the Power BI Service. The cases come from the same family as those used in IBA's PL-300 training; a different case from the organisation's own dataset (sales, finance, operations, etc.) can also be proposed — provided it is of similar scope, this does not affect the duration or price of the training. The organisation can later take this case to an advanced level with PL-300, including DAX, RLS and scheduled refresh.

03Training Agenda (2 Days)

The agenda builds up the chosen case day by day; the first day focuses on connecting data and modelling, the second on visualisation and sharing.

  1. Day 1 — Connecting Data and the Basic Model

    • Introduction to Power BI Desktop and its interface
    • Exercise 1: Connecting the case data to Power BI Desktop and cleaning it with Power Query
    • The concept of relationships between tables
    • Exercise 2: Building a simple data model with relationships between tables
    • Basic aggregation measures
    • End-of-Day Deliverable: Completing a working basic data model

  2. Day 2 — Visualisation, Interaction and Sharing

    • Basic visualisation types and choosing the right chart
    • Exercise 3: Creating a basic set of visuals for the case data
    • Adding interaction with filters and slicers
    • Exercise 4: Making the report interactive with filters/slicers
    • Introduction to the Power BI Service and publishing steps
    • Final Deliverable: Publishing and sharing the report in the Power BI Service
    • Overall review, Q&A and certificate presentation

04Technical Requirements

Computer

1 per participant (Windows or macOS), with internet access

Software Installation

Power BI Desktop (free) — must be installed before the training

Browser

Microsoft Edge or Google Chrome — for the Power BI Service steps

Account

Microsoft work/school account, or a Power BI Pro trial account opened for the training

Licensing

No licence purchase is required for this training.

Power BI Desktop is completely free, and all data connection, modelling and visualisation work is carried out in it.

Microsoft's free Pro trial licence is used for the sharing steps in the Power BI Service; this adds no cost to the organisation's existing Microsoft 365 licences.

05Learning Outcomes

Connect data

Connect their own department's raw data to Power BI and clean it.

Build a simple model

Create a basic data model by setting up relationships between tables.

Prepare reports

Design a basic visual report using the right chart types.

Add interaction

Make a report interactive with filters and slicers.

Share

Publish a report in the Power BI Service and share it with the relevant people.

PL-300 (Power BI Advanced)

Data Analysis and Visualisation Training

4 DaysGet a Quote

01Training Overview

Duration
4 Days
Training Hours
09:30 – 16:30
Maximum Participants
10 Participants
Hands-on Ratio
80% Hands-on / 20% Theory
Certificate
Participants receive an IBA Consultancy Certificate of Participation at the end of the training.
Format
Online, On-site or Hybrid — set according to the organisation's preference.
Prerequisites
No software development knowledge is required. Basic Excel skills (formulas, working with tables) are recommended.
Training Objective

This training gives participants the ability to manage an end-to-end data analysis process on the Power BI platform. Throughout the programme, participants learn data connection and cleaning, relational data modelling, writing calculations with DAX and interactive dashboard design by working on a real dataset.

The training covers the full process from raw data to a dashboard ready for management presentation. In their chosen case, participants first connect the data and build its model, then write DAX measures that answer business questions, and finally bring these measures together in an interactive dashboard and share it securely through the Power BI Service.

By the end of the training, participants are report developers who can build their own story from their own data rather than applying ready-made templates.

Technical Content

Data Preparation and Modelling

  • The Power BI ecosystem: how Desktop, Service and Gateway relate
  • Licensing models: differences between Free, Pro and Premium
  • Connecting to data sources (Excel, SQL, SharePoint, web)
  • Cleaning and transforming data with Power Query
  • Editing queries and the logic of applied steps
  • Building a relational data model: table relationships and cardinality
  • Introduction to star schema

DAX and Analysis

  • The difference between calculated columns and measures
  • Core DAX functions: SUM, CALCULATE, FILTER
  • Time Intelligence functions: YTD, MTD, period-over-period comparison
  • Performance analysis visuals: KPI, Gauge, Top N

Visualisation, Sharing and Governance

  • Chart types and principles for choosing the right visual
  • Interaction with filtering, slicers and bookmarks
  • Publishing to the Power BI Service and workspace management
  • Gateway setup and automatic data refresh
  • Role-based data security (Row-Level Security)

02Exercises and Project Scenarios

Option A

Management Performance Dashboard

A dashboard tracking senior management metrics such as subscriber/member numbers, revenue, churn and growth. It is extended with time-based comparisons and KPI tracking.

Option B

Sales and Stock Performance Dashboard

A dashboard tracking sales, stock turnover and campaign impact by store/category. It is extended with regional comparison and slicer-based analysis.

Whichever case is chosen, the technical scope and outcomes of the training stay the same — the same Power Query, data modelling, DAX and dashboard design topics are covered. A single dashboard case is chosen for the training and built up step by step over the four days: on Day 1, the data source is connected and cleaned and the basic relational model is built; on Day 2, basic DAX measures and the first set of visuals are added; on Day 3, advanced DAX (time-based analysis) and interactive dashboard design are added; on Day 4, the sharing, automatic refresh and data security layer is set up. A different case from the organisation's own dataset (sales, finance, operations, etc.) can also be proposed — provided it is of similar scope, changing the scenario does not affect the duration or price of the training.

03Training Agenda (4 Days)

The agenda works through the dashboard case chosen before the training. Every step below that mentions "the chosen case" is applied to the scenario the organisation prefers (Management Performance Dashboard / Sales and Stock Performance Dashboard, or an organisation-specific dataset).

  1. Day 1 — Data Connection, Cleaning and Building the Basic Model

    • The Power BI ecosystem: how Desktop, Service and Gateway relate
    • Licensing models: differences between Free, Pro and Premium
    • Connecting to data sources (Excel, SQL, SharePoint, web)
    • Cleaning and transforming data with Power Query
    • Editing queries and the logic of applied steps
    • Building a relational data model: table relationships and cardinality
    • Introduction to star schema
    • Exercise 1: Connecting the chosen case to its data source and cleaning the data
    • Exercise 2: Creating relationships between tables

  2. Day 2 — Calculations with DAX and Basic Visualisations

    • Introduction to DAX: the difference between calculated columns and measures
    • Core DAX functions: SUM, CALCULATE, FILTER
    • Exercise 3: Writing basic measures that answer business questions
    • Basic visuals: Card, Pie Chart, Table
    • Chart types: Column, Line, Scatter, Funnel
    • Principles for choosing the right chart for the right data
    • Exercise 4: Creating the first set of visuals
    • Visual formatting and on-brand design

  3. Day 3 — Advanced DAX and Interactive Dashboard Design

    • Time Intelligence functions: YTD, MTD, year-on-year comparison
    • Exercise 5: Writing time-based analysis measures
    • Performance analysis visuals: KPI, Gauge, Top N
    • Exercise 6: Building a performance indicator panel
    • Filtering, slicers and page-level interaction
    • Switching between scenario-based views with bookmarks
    • Exercise 7: Completing the interactive dashboard
    • Introduction to Power BI integration with Power Apps

  4. Day 4 — Sharing, Governance and Final Deliverable

    • Publishing to the Power BI Service and workspace management
    • Exercise 8: Publishing the report to the Service
    • Gateway setup and automatic data refresh
    • Exercise 9: Designing a scheduled refresh plan
    • Role-based data security (Row-Level Security)
    • Exercise 10: Defining department-based data access with RLS
    • Sharing, permission management and turning dashboards into an app
    • Final Deliverable: End-to-end testing and publishing of the chosen case
    • Overall review, Q&A and certificate presentation

04Technical Requirements

Computer

1 per participant (Windows or macOS), with internet access

Software Installation

Power BI Desktop (free) — must be installed before the training

Browser

Microsoft Edge or Google Chrome — for the Power BI Service steps

Account

Microsoft work/school account, or a Power BI Pro trial account opened for the training

Licensing

No licence purchase is required for this training.

Power BI Desktop is completely free, and all data connection, modelling, DAX and visualisation work is carried out in it.

Microsoft's free Pro trial licence is used for the sharing and automatic refresh steps in the Power BI Service; this adds no cost to the organisation's existing Microsoft 365 licences.

05Learning Outcomes

Develop reports

Connect and clean raw data and turn it into a dashboard ready to present to management.

Build a data model

Link multiple tables with the correct relationship types.

Write calculations

Create DAX measures that answer business questions (growth rate, period-over-period comparison).

Design dashboards

Create user-friendly screens that support decision-making, with filtering and interaction.

Publish

Move a report to the Power BI Service and share it securely.

Keep data up to date

Set up a live data connection with a Gateway and schedule automatic refresh.

Microsoft Fabric Basic

Introduction to End-to-End Data Analytics — Beginner Training

4 DaysGet a Quote

01Training Overview

Duration
4 Days
Training Hours
09:30 – 16:30
Maximum Participants
12 Participants
Hands-on Ratio
80% Hands-on / 20% Theory
Certificate
Participants receive an IBA Consultancy Certificate of Participation at the end of the training.
Format
Online, On-site or Hybrid — set according to the organisation's preference.
Prerequisites
No software development knowledge is required. Basic knowledge of data/tables and basic Excel skills are sufficient; SQL and Power BI experience is useful but not required.
Training Objective

This training gives participants a hands-on understanding of Microsoft Fabric's role in the enterprise data platform and of the end-to-end analytics process, from a data source through to a management report. Throughout the programme, participants learn OneLake architecture, Lakehouse and Warehouse concepts, data preparation with Dataflow Gen2 and Pipeline, data engineering with Notebook and Spark, and reporting with Semantic Model and Power BI by doing the work themselves.

The key difference of this training is that the topics are covered through a single real business scenario rather than disconnected examples. A case is chosen with the organisation before the training and built up step by step over the four days: raw data is brought into Fabric, cleaned and modelled, and then a Power BI report meeting enterprise standards is built on top of it.

The first three days are devoted to Fabric's data layer (OneLake, Lakehouse, Warehouse, Pipeline, Notebook); on the fourth day, the data from the chosen case is turned into a data model and an interactive report with Power BI. Participants experience the process end to end, from source to management report.

By the end of the training, participants are data practitioners who can produce an enterprise management report from raw data, not just process it.

Technical Content

Microsoft Fabric Platform and Architecture

  • Explaining the shift from traditional data warehouse and data lake approaches to a SaaS-based unified analytics platform
  • Introducing Tenant, Capacity and Workspace concepts and the Fabric portal through role-based usage scenarios
  • Comparing which need each component serves: OneLake, Lakehouse, Warehouse, Data Factory, Notebook/Spark, Semantic Model, Power BI and Real-Time Intelligence
  • Hands-on demonstration of the difference between the Files and Tables areas in OneLake, the Delta Lake table structure, and accessing data without copying it using Shortcuts

Data Ingestion and Data Preparation with Dataflow Gen2

  • Comparing manual file upload, Dataflow Gen2, Pipeline Copy Activity, Notebook and Shortcut methods by scenario
  • Hands-on data source connection, data type editing, filtering, and Merge and Append operations in the Power Query Online interface
  • Handling errors and null values, setting a data destination, running the Dataflow and validating the results
  • Loading data from Excel/CSV/a relational database into a Lakehouse and converting it into a Delta table

Pipeline, Notebook, Spark and Delta Lake

  • The difference between Pipeline and Dataflow, connecting source and destination with Copy Activity, and designing activity dependencies
  • Designing a scheduled data load scenario with a Schedule Trigger and carrying out basic error analysis by monitoring pipeline run history
  • Introduction to how Apache Spark and Notebooks work; reading a Lakehouse table with PySpark DataFrame and Spark SQL
  • Hands-on null value checks, creating a new calculated column and writing the result to a new Delta table

Relational Modelling with Warehouse

  • Explaining how Fabric Warehouse differs from Lakehouse and which to choose in which scenario
  • Hands-on creation of tables, loading data and defining Views with T-SQL
  • Introduction to Fact and Dimension tables and demonstrating the Star Schema approach on a sample data model

Data Modelling and Reporting with Power BI

  • How Power BI Desktop, Power BI Service and Fabric relate; comparing the Import, DirectQuery and Direct Lake connection methods
  • Connecting to Fabric Lakehouse/Warehouse data and, with Power Query, hands-on filtering, splitting/merging columns, conditional columns and Merge/Append operations
  • Building a Star Schema data model from Fact and Dimension tables; one-to-many relationships, active/inactive relationships and date table design
  • Developing basic DAX measures using the difference between measures and calculated columns, Filter/Row Context, the CALCULATE function and variables
  • Creating a report page that meets enterprise design standards with KPI cards, line/column charts, matrix and map visuals
  • Designing an interactive report experience with slicers, drill-down, drill-through, tooltips, bookmarks and button navigation
  • Publishing the report in the Power BI Service or a Fabric Workspace and managing sharing and access permissions

Fabric and Power BI with Copilot (covered hands-on in the relevant modules across all 4 days)

  • Using Fabric Copilot to create Dataflow queries, generate/explain Notebook code and write SQL queries
  • Using Copilot to develop DAX measures, explain existing measures and summarise report content
  • Using Power BI Copilot to get report page and visual suggestions and ask questions about data in natural language
  • Emphasising the need to validate Copilot output and the points to watch for enterprise data security; feature availability may vary depending on the organisation's Fabric capacity, tenant settings and licensing

02Exercises and Project Scenarios

Option A

Sales and Stock Analysis System

A system in which retail sales data (FactSales, DimDate, DimProduct, DimStore, DimCustomer, DimCategory) is brought into Fabric and turned into a Star Schema model, on top of which a Power BI report is built with executive summary, sales analysis and stock analysis pages. It is extended with total sales, profit margin, target achievement rate and critical stock alerts.

Option B

Production and Operations Reporting System

A system in which data from production lines or operational systems is collected and cleaned in a Lakehouse, and production volume, downtime and efficiency indicators are moved into a relational model in a Warehouse. It is extended with periodic production reports and an operations dashboard.

Option C

Financial Performance Reporting System

A system in which income and expense data from an accounting/ERP system is combined in Fabric and turned into a budget-versus-actual data model. It is extended with department-level cost analysis and a board report.

Whichever case is chosen, the technical scope and outcomes of the training stay the same; the same Fabric data layer and Power BI reporting topics are covered. On Day 1, the chosen case's data is brought into a Fabric Workspace and Lakehouse and cleaned with Dataflow Gen2; on Day 2, the data load process is automated with a Pipeline and data engineering is applied with Notebook/Spark; on Day 3, the data is moved into a relational structure (Fact/Dimension) in a Warehouse and the Power BI foundation is laid with a Semantic Model; on Day 4, an enterprise Power BI report is built on the prepared data and published. The organisation's own process can also be used as the case; provided it is of similar scope, this does not affect the duration or price of the training. Where real organisational data is used, masking or anonymising personal and sensitive data is recommended.

03Training Agenda (4 Days)

The agenda works through the project case chosen before the training. Every step below that mentions "the chosen case" is applied to the scenario the organisation prefers (Sales and Stock Analysis / Production and Operations / Financial Performance, or an organisation-specific process).

  1. Day 1 — Microsoft Fabric Fundamentals and Data Integration

    • The shift from traditional data warehouse structures to Fabric's unified, SaaS-based analytics platform approach
    • Tenant, Capacity and Workspace concepts and an introduction to the Fabric portal
    • An overview map of Fabric components (OneLake, Lakehouse, Warehouse, Data Factory, Notebook/Spark, Semantic Model, Power BI, Real-Time Intelligence, Copilot)
    • How OneLake works, the Files/Tables distinction and an introduction to the Delta Lake table structure
    • Comparing methods for bringing data into Fabric (manual upload, Dataflow Gen2, Pipeline, Notebook, Shortcut)
    • Exercise 1: Creating a Fabric Workspace and Lakehouse for the chosen case, loading the source data, converting it into a Delta table and querying it through the SQL Analytics Endpoint
    • Data source connection, filtering, and Merge and Append operations with Dataflow Gen2 in Power Query Online
    • Exercise 2: Cleaning the chosen case's data with Dataflow Gen2
    • End-of-Day Deliverable: Lakehouse and Warehouse compared and scenarios for choosing a data ingestion method assessed

  2. Day 2 — Data Engineering with Pipeline, Notebook, Spark and Warehouse

    • The Pipeline concept, how it differs from Dataflow, and connecting source and destination with Copy Activity
    • Activity dependencies, pipeline parameters and scheduled data loads with a Schedule Trigger
    • Exercise 3: Designing a scheduled data load flow for the chosen case with a Pipeline
    • How Apache Spark and Notebooks work; introduction to PySpark DataFrame and Spark SQL
    • Exercise 4: Reading a Lakehouse table as a DataFrame, checking for nulls, creating a new column and writing the result to a Delta table
    • The Fabric Warehouse concept, how it differs from Lakehouse, and creating tables/defining Views with T-SQL
    • Introduction to Fact and Dimension tables and the Star Schema approach
    • Exercise 5: Moving the chosen case into Fact/Dimension tables in the Warehouse
    • End-of-Day Deliverable: Pipeline error analysis carried out and Star Schema design checked

  3. Day 3 — Semantic Model, Power BI Fundamentals and Fabric Copilot

    • The Semantic Model concept, Fabric and Power BI integration, and an introduction to Direct Lake
    • How Power BI Desktop, Service and Fabric relate; the Import, DirectQuery and Direct Lake connection methods
    • Exercise 6: Connecting to Fabric Lakehouse/Warehouse data from Power BI Desktop and identifying the tables needed for modelling
    • Table relationships, the difference between measures and calculated columns, and basic DAX measures (sum, average, ratio)
    • Using a date table and the logic of period-based analysis
    • Exercise 7: Creating the basic data model and first DAX measures for the chosen case
    • Using Fabric Copilot to create Dataflow queries, generate/explain Notebook code and write SQL queries
    • Using Copilot to develop DAX measures and the need to validate its output
    • End-to-End Mini Project: combining the steps source data ingestion → Dataflow Gen2 → Pipeline → Lakehouse/Warehouse tables → Semantic Model on the chosen case

  4. Day 4 — Data Modelling, Reporting and Copilot with Power BI

    • Applying filtering, splitting/merging columns, conditional columns and Merge/Append operations with Power Query in the report-specific layer
    • Completing the Star Schema model from Fact/Dimension tables: one-to-many relationships, active/inactive relationships, single/bidirectional filtering
    • Exercise 8: Building the chosen case's sample data model (Fact and Dimension tables) in Power BI and completing the relationships
    • Advanced DAX measures with the CALCULATE function, variables, safe division and blank value checks
    • Enterprise report design principles: page layout, visual hierarchy, KPI cards, conditional formatting, dynamic titles
    • Exercise 9: Designing an executive summary page, a detailed analysis page and a second analysis page for the chosen case
    • Designing an interactive report with slicers, drill-down, drill-through, tooltips, bookmarks and button navigation
    • Exercise 10: Adding navigation between pages, drill-through and dynamic titles
    • Using Power BI Copilot to get report page/visual suggestions, prepare DAX measures and query data in natural language
    • Publishing the report in the Power BI Service / a Fabric Workspace and managing sharing and access permissions
    • Final Deliverable: End-to-end testing (Fabric data layer → Power BI report) and publishing of the chosen case, overall review and certificate presentation

04Technical Requirements

Computer

1 per participant (Windows or macOS), with an uninterrupted internet connection

Software

Power BI Desktop and an up-to-date web browser

Access

Microsoft Fabric access, the tenant and trial environment, and participant Workspace permissions for the training are provided by the organisation. Where these systems are not already in place, the trainer can help with the setup.

Licence (Copilot)

A Fabric licence is mandatory to use Fabric Copilot features.

Licensing

No additional licence purchase is required for the core Fabric and Power BI content of the training; the work can be done on a Fabric trial capacity.

However, for the Copilot modules (Fabric Copilot and Power BI Copilot) to be covered hands-on, the organisation must have a valid Fabric licence.

Power BI Desktop is free to install; to publish the report to a Workspace, participants need the appropriate Workspace permissions.

05Learning Outcomes

Set up a data platform

Bring the organisation's data sources together in a single environment by creating a Fabric Workspace and Lakehouse/Warehouse.

Prepare data

Clean raw data with Dataflow Gen2 and Pipeline and load it into Fabric on a schedule.

Do data engineering

Carry out basic data transformations with Spark in a Notebook and write them to a Delta table.

Build a data model

Design a Star Schema model of Fact and Dimension tables and set up the correct relationships.

Develop reports

Prepare and publish an interactive Power BI report with DAX measures from their own department's data.

Make use of Copilot

Use Fabric and Power BI Copilot features to generate queries, code and reports, and validate the output.

Microsoft Fabric Advanced

Enterprise Data Engineering and Analytics Solutions — Advanced Training

5 DaysGet a Quote

01Training Overview

Duration
5 Days
Training Hours
09:30 – 16:30
Maximum Participants
10 Participants
Hands-on Ratio
80% Hands-on / 20% Theory
Certificate
Participants will receive an IBA Consultancy Certificate of Participation at the end of the training.
Format
Online, On-site or Hybrid — based on the organisation's preference.
Prerequisites
Knowledge at the level of the Microsoft Fabric Beginner Training (Fabric core components, SQL querying, data warehousing and dimensional modelling, Power BI data modelling, basic ETL processes) or equivalent experience is recommended.
Training Objective

This training aims to take the foundations laid in Fabric Beginner to the level where participants can build a production-ready data platform at enterprise scale. Throughout the programme, participants move the data of the case chosen in Fabric Beginner into a Medallion architecture made up of Bronze, Silver and Gold layers, develop metadata-driven parameterised pipelines, apply PySpark/Spark SQL transformations in Notebooks, and build an enterprise Power BI solution on top with a Direct Lake-compatible Semantic Model.

What sets this training apart is that topics are not covered through disconnected examples but by scaling the case chosen in Fabric Beginner up to enterprise level. Over five days, the same case is expanded step by step with data integration, data engineering, data warehousing, security and lifecycle management layers.

For participants who have not taken Fabric Beginner, the same case options (Sales and Stock Analysis / Production and Operations / Financial Performance) are set up quickly on the first day and built upon.

By the end of the training, participants do not just have a simple reporting solution; they own a production-ready enterprise Fabric platform equipped with security, monitoring and DevOps processes.

Technical Content

Enterprise Fabric Architecture and the Medallion Approach

  • Designing the Tenant, Capacity, Domain and Workspace organisation to enterprise standards; separating Development, Test and Production environments
  • Making the right architectural choice between Lakehouse, Warehouse and Eventhouse for each use case, and applying data discovery with OneLake Catalog
  • Building a Medallion architecture of Bronze, Silver and Gold layers; separating the responsibility of each layer (raw data storage, cleansing/standardisation, applying business rules)
  • Batch and streaming data ingestion, full/incremental load strategies, and comparing Pipeline, Copy Job, Dataflow Gen2 and Notebook approaches by scenario

Metadata-Driven and Parameterised Pipeline Development

  • Designing dynamic flows using pipeline parameters, Lookup and ForEach activities, and If Condition/Switch
  • Hands-on parameterised loading of multiple tables using a parent-child pipeline structure and a metadata control table
  • Setting up trigger and schedule management, error handling and notification processes to enterprise standards

Data Engineering with Fabric Spark

  • Hands-on demonstration of Fabric Spark architecture, Driver/Executor concepts, Lazy Evaluation and partitioning using PySpark DataFrames
  • Data transformation with Select, Filter, WithColumn, Join, GroupBy/Aggregate and Window Functions; data quality checks with null/duplicate handling and schema validation
  • Temporary Views, CTEs and cross-layer data transformations with Spark SQL, compared with the DataFrame API

Delta Lake Management

  • Hands-on demonstration of the Delta Transaction Log, ACID transactions and Schema Enforcement/Evolution in the Bronze-Silver-Gold flow
  • Developing incremental load processes with Merge, Update, Delete and Upsert scenarios
  • Partition strategies, table maintenance, Time Travel and the small-file problem from a performance optimisation perspective

Data Warehouse and Dimensional Modelling

  • Comparing Lakehouse and Warehouse use cases through SQL Endpoint, T-SQL, Stored Procedure and View capabilities
  • Dimensional data model design with Star Schema and Snowflake Schema, Surrogate/Natural Keys, grain definition and Slowly Changing Dimensions
  • Building Fact and Dimension tables in the Gold layer, and centralising data quality metrics and business rules

Semantic Model, Direct Lake and Power BI

  • Comparing Import, DirectQuery and Direct Lake connection modes; building a Direct Lake-compatible Semantic Model on the Gold layer
  • Developing basic and advanced DAX measures with the Measure Table approach and Calculation Groups
  • Preparing a secured management report with Row-Level Security and Object-Level Security and sharing it through a Fabric Workspace

Fabric Security, DevOps and Monitoring

  • Planning permissions at Tenant/Capacity/Workspace/Item level, Workspace roles (Viewer/Contributor/Member/Admin) and OneLake security
  • Controlled content promotion between Development, Test and Production environments with Deployment Pipelines; introduction to Git integration and branching strategies
  • Monitoring pipeline/notebook/Semantic Model run history via the Monitoring Hub; log table design and source-to-target row count reconciliation

Capacity Management and Real-Time Intelligence (covered hands-on on Day 5)

  • Fabric Capacity and the Capacity Unit concept; assessing how pipeline, Spark and Semantic Model workloads affect resource consumption
  • Introduction to real-time analytics with Eventstream, Eventhouse, KQL Database and Real-Time Dashboard; operational alert scenarios with Activator

02Exercises and Project Scenarios

Option A

Sales and Stock Analysis System

The sales and stock analysis system built in Fabric Beginner is scaled up to enterprise level by moving SQL Server sales transactions, Excel product targets, CSV store/stock information, and customer and campaign data into the Bronze-Silver-Gold layers. It is turned into a management report secured with Row-Level Security by region and store manager.

Option B

Production and Operations Reporting System

The production/operations reporting system built in Fabric Beginner is scaled up to enterprise level by layering production line, downtime and efficiency data with a Medallion architecture. Periodic production reports are automated with parameterised pipelines and incremental loading.

Option C

Financial Performance Reporting System

The financial performance system built in Fabric Beginner is scaled up to enterprise level by ingesting accounting/ERP data into the Bronze-Silver-Gold layers and moving it into a dimensional model. It is turned into a board report secured with Row-Level Security by department.

Whichever case is chosen, the technical scope and outcomes of the training stay the same; the same Medallion architecture, parameterised pipeline, Spark/Delta Lake and Direct Lake Semantic Model topics are covered. On Day 1, the data sources of the chosen case are brought into the enterprise Fabric architecture and loaded into the Bronze layer with a metadata-driven parameterised pipeline; on Day 2, the Silver and Gold layers are built with Notebooks/Spark and Delta Lake; on Day 3, a dimensional data model is built on the Gold layer, along with a Direct Lake-compatible Semantic Model and a Power BI management report; on Day 4, the solution is secured with Row-Level Security and made production-ready with Deployment Pipelines and monitoring mechanisms; on Day 5, capacity optimisation and, where needed, Real-Time Intelligence components are added and teams present the solution end to end. The organisation's own process can also be used as the case; provided it is of similar scope, this does not affect the duration or price of the training.

03Training Agenda (5 Days)

The agenda is delivered by scaling the project case chosen in Fabric Beginner (or before the training) up to enterprise level. Every step below that refers to "the chosen case" is applied to the organisation's preferred scenario (Sales and Stock Analysis / Production and Operations / Financial Performance, or an organisation-specific process).

  1. Day 1 — Enterprise Fabric Architecture and Data Integration

    • Tenant, Capacity, Domain and Workspace organisation; designing Development/Test/Production environments to enterprise standards
    • Choosing between Lakehouse, Warehouse and Eventhouse; data discovery with OneLake Catalog
    • Medallion architecture: the purpose and responsibilities of the Bronze, Silver and Gold layers
    • Batch/streaming data ingestion, full/incremental load strategies; comparing Pipeline, Copy Job, Dataflow Gen2 and Notebook
    • Pipeline parameters, Lookup/ForEach activities, If Condition/Switch and the parent-child pipeline structure
    • Exercise 1: Creating a metadata control table for the chosen case and loading multiple source tables into the Bronze layer with parameters
    • Exercise 2: Logging successful/failed loads and recording pipeline run information

  2. Day 2 — Data Engineering with Fabric Spark, PySpark and Delta Lake

    • Fabric Spark architecture: Driver/Executor, Lazy Evaluation, Transformation/Action and partition concepts
    • Data transformation with PySpark using Select/Filter/WithColumn, Join, GroupBy/Aggregate and Window Functions
    • Handling null/duplicate values, schema validation and data quality checks; reusable transformation functions
    • Temporary Views, CTEs and cross-layer data transformation with Spark SQL, compared with the DataFrame API
    • Delta Lake architecture: Transaction Log, ACID transactions, Schema Enforcement/Evolution
    • Exercise 3: Reading the chosen case from the Bronze layer and producing clean data in the Silver layer with schema/data type checks and separation of invalid records
    • Exercise 4: Incremental loading with Delta Merge and adding technical audit columns
    • Exercise 5: Building Gold layer tables by applying business rules

  3. Day 3 — Data Warehouse, Dimensional Modelling and Power BI

    • Lakehouse and Warehouse design decisions; using SQL Endpoint, T-SQL, Stored Procedures and Views
    • Dimensional data modelling: Star Schema, Snowflake Schema, Surrogate/Natural Keys, grain definition, Slowly Changing Dimensions
    • Exercise 6: Building Fact and Dimension tables in the Gold layer for the chosen case, and centralising data quality metrics and business rules
    • Semantic Model architecture: comparing Import, DirectQuery and Direct Lake; how Direct Lake works
    • Measure Table approach, Calculation Groups and DAX measure development (basic and advanced)
    • Exercise 7: Creating a Direct Lake-compatible Semantic Model from the Gold layer, setting up Fact/Dimension relationships and preparing DAX measures
    • Exercise 8: Creating a Row-Level Security role, preparing the management report and sharing it through a Fabric Workspace

  4. Day 4 — Fabric Security, DevOps and Monitoring

    • Permissions at Tenant/Capacity/Workspace/Item level; Workspace roles (Viewer/Contributor/Member/Admin)
    • Overview of Row-Level Security, Object-Level Security, OneLake security, sensitivity labels and Microsoft Purview integration
    • Exercise 9: Defining department/region-based access rules at Workspace and OLS/RLS level for the chosen case
    • Promoting content between Development, Test and Production environments with Deployment Pipelines; Deployment Rules
    • Introduction to Git integration: branching strategies, source control, notebook/pipeline version management
    • Exercise 10: Setting up a Deployment Pipeline for the chosen case's solution and running a test-to-production promotion scenario
    • Monitoring pipeline/notebook/Semantic Model run history with the Monitoring Hub; log table design, Run ID usage, retry and alert mechanisms
    • Exercise 11: Building a data quality log mechanism that checks source-to-target row count reconciliation

  5. Day 5 — Capacity, Real-Time Intelligence and End-to-End Project

    • Fabric Capacity and the Capacity Unit concept; how pipeline, Spark and Semantic Model workloads affect resource consumption
    • Query and model optimisation, data size/partition strategy, and balancing cost and performance through capacity monitoring
    • Introduction to Real-Time Intelligence: Eventstream, Eventhouse, KQL Database/Queryset, Real-Time Dashboard and Activator
    • Exercise 12 (optional): Trying out a simple real-time data stream with Eventstream for the chosen case
    • End-to-End Enterprise Project: analysing source system and reporting requirements, designing the Workspace/Lakehouse architecture
    • Final Deliverable: Integrating the chosen case end to end with Bronze-Silver-Gold layers, parameterised pipelines, a Semantic Model and RLS security, presented by the teams
    • General review, Q&A and certificate presentation

04Technical Requirements

Computer

1 per participant (Windows or macOS), with an uninterrupted internet connection

Software

Power BI Desktop and an up-to-date web browser

Access

Microsoft Fabric access for the training, a tenant and trial environment, and participant Workspace permissions are provided by the organisation. Where these are not already in place, the trainer can support the setup process.

Data Source Access

Sample datasets for the chosen case (SQL Server, Excel, CSV, etc.) or the organisation's own test data should be ready before the training.

Licensing

No additional licence purchase is needed for the core content of the training; the work can be done on a Fabric trial capacity.

However, to fully test Deployment Pipelines, Git integration and Real-Time Intelligence components at enterprise scale, it is recommended that the organisation has a valid Fabric Capacity licence.

Power BI Desktop is free to install; to publish and share the report in a Workspace, participants need the appropriate Workspace permissions.

05Learning Outcomes

Design an enterprise architecture

Set up the Tenant/Capacity/Domain/Workspace organisation and a Medallion (Bronze/Silver/Gold) layer architecture to enterprise standards.

Develop metadata-driven pipelines

Load multiple sources automatically and traceably with parameterised pipelines driven by a metadata control table.

Carry out data engineering

Apply Bronze-to-Gold data transformations with PySpark and Spark SQL and set up incremental loading with Delta Lake.

Build a dimensional data model

Design a Gold layer of Fact/Dimension tables following Star Schema principles, and a Direct Lake-compatible Semantic Model.

Set up security and governance

Publish a report secured with Row-Level Security and Object-Level Security, in line with organisational sharing policies.

Move to production

Promote the solution from development to test and production environments in a controlled way using Deployment Pipelines and monitoring mechanisms.

Frequently Asked Questions

The training period is determined as 2 days for the beginner level and 4 days for the advanced level. This period is ideal for detailed treatment of the subjects and practical applications. Flexible hours are offered to suit the busy schedules of the participants.

Trainings are carried out interactively with experienced trainers. Both theoretical information and practical work are presented together. Remote participation is also possible with the Power BI training online option. Training materials and resources are provided to participants digitally.

Anyone who wants to improve themselves in data analysis and reporting can participate. It is ideal for business analysts, data experts, IT professionals and managers. It is also suitable for those who are just starting their career and want to specialize in this field. Power BI course brings together participants from different sectors.

Basic computer knowledge and familiarity with Excel are sufficient. It is advantageous for those with previous data analysis experience, but it is not required. The training content is designed to be easily understood by participants of all levels. In this way, even beginners can easily follow.

Participants are given a certificate of achievement when the case studies in the training programs are completed with the effective application of the determined concept. In cases where the concept studies are not applied, participants are certified with a participation certificate documenting their involvement in the process.

The beginner level runs 4 days and the advanced level 5 days. Training hours are 09:30 to 16:30.

It can be delivered online, on site or hybrid. The format is set according to your preference.

The beginner level needs no development background; basic data/table knowledge and basic Excel are enough. The advanced level assumes beginner-level Fabric knowledge or equivalent experience.

The program is 80% practice and 20% theory. A single case from your organisation is grown step by step throughout the training.

Up to 12 participants at beginner level and up to 10 at advanced level.

Yes. Participants receive an IBA Consultancy Certificate of Attendance at the end of the training.