Power BI

Power BI

Power BI, from raw data to decisions- Power Query, star schema, dashboards

About the Power BI Training

Power BI autonomy in 2 days, from data to sharing

Our Power BI training is designed for teams with mixed skill levels, with one clear goal: becoming autonomous across the full Power BI workflow, from raw data to publishing reliable, usable reports.

In practice, participants learn to:

  • use a report as an advanced end user,
  • build KPIs with DAX,
  • design interactive reports,
  • prepare and model data following BI best practices,
  • publish and share in Power BI Service / Fabric.
eaQbe methodology: progressive skill-building

We don’t believe in trainings that stack feature after feature. We focus on structured immersion, guided by a scenario-based throughline: participants learn the Power BI flow in the right order and develop habits that last.

Our approach follows a progressive logic:

  • Understand before you build
  • Use before you implement
  • See the end goal before diving into technical details
Learning path

1) Use Power BI like an advanced end user

Before building, participants learn how to work with a report properly: navigation, filters, interactions, drill-down/drill-through, and interpreting visuals and KPIs. The goal is to understand what a good report must enable—and how users actually interact with information.

2) DAX & KPI design

Starting from a clean, pre-built model, participants learn the right DAX fundamentals: measures vs columns, essential functions, and KPI logic. The goal is to create KPIs that are reliable, readable, and reusable.

3) Data visualization & decision-ready reporting

Once KPIs are in place, participants focus on data visualization: page structure, visual selection, report design, and interactivity (filters, buttons, bookmarks, drill-through). They learn how to deliver reporting that is clear, consistent, and adopted.

4) Power Query & modeling (data architecture)

Finally, we go back “to the start”: unprepared data, Power Query transformations, then modeling (star schema, relationships, cardinality, filter direction) to build a model that is performant and maintainable.

Continuous skills validation

Throughout the training, participants validate what they’ve learned through short explain-back moments and guided reviews—so the goal is real, transferable understanding, not just “having seen it once.”

Skills gained
  • Practical DAX: build relevant measures, master the “measures vs columns” logic, and apply the first essential patterns.
  • Report autonomy: use, maintain, evolve, and adapt Power BI reports with confidence.
  • Interactive, consistent reporting: structure pages, manage navigation and interactions, and deliver clear outputs.
  • Solid BI modeling: star schema, relationships, cardinality, filter direction.
  • From data to sharing: prepare/model, then publish and share in Power BI Service / Fabric with a clear distribution approach.
Practical details
  • Format: 2-day intensive workshop (hands-on & scenario-based)
  • Group size: 5–10 participants (small groups for personalized coaching)
  • Prerequisites: none
  • Follow-up: evaluation + post-training anchoring exercises

Data visualization & storytelling

1.1 Modern BI foundations

General introduction

  • The strategic role of BI in decision-making
  • Data types: structured vs semi-structured
  • Key concepts: dimensions vs measures
  • Introduction to star schema and ETL logic (Extract, Transform, Load)
1.2 The “end-user” experience

Getting started with Power BI and becoming familiar with the different environments:

  • Power BI Desktop: report building + Power Query integration
  • Fabric + Power BI Service: workspaces, dashboards, apps
1.3 Report building, visualization & DAX

Learning how to enrich analysis and visuals with DAX:

  • Create calculated columns, measures, and tables
  • Create and configure standard and advanced visuals
  • Add interactivity: drill-through, slicers, buttons, bookmarks, parameters, and What-If scenarios

Data architecture & engineering

2.1 Power Query & ETL logic

Understanding how data is extracted, why it must be prepared, and how to transform it:

  • The role of Power Query within Power BI
  • ETL concept (Extract, Transform, Load)
  • Data connections & gateways
2.2 Data transformation & cleaning

Hands-on data preparation:

  • Clean, format, and manage data types
  • Create calculated columns or transform existing ones
  • Filter, standardize, and unpivot
2.3 Building a star schema (modeling)
  • Fact tables vs dimension tables
  • Combine data: append (adding rows) vs merge (left/inner/full outer joins)
  • Manage relationships, cardinality, and filter direction
  • Optimize the model for faster analysis

Build capability, not dependency

Richard Feynman nailed it: “If you can’t explain it simply, you don’t understand it well enough.”

That’s eaQbe’s DNA. We don’t just train your team on data  tools. We build experts who can explain, apply, and amplify what they’ve learned.