Duration 4 Days – 28 hrs.

 

Overview

This Phase 1 course is a practical, hands-on program that builds core Power BI development skills and grows them into advanced dashboarding capability. It is designed for participants who already work with spreadsheets and reports and are ready to move into Power BI as their primary analysis and reporting tool.

The course follows a deliberate progression across four intensive days: core Power BI skills (connecting to data, shaping it in Power Query, modeling it, and writing foundational DAX), then storytelling, communication, and visualization craft, then advanced dashboarding techniques such as advanced DAX, performance optimization, and row-level security, and finally the basic SQL skills needed to query and understand source systems directly.

Participants will work hands-on in Power BI Desktop throughout the course, using realistic business datasets to build a working data model, a library of DAX measures, and a multi-page dashboard. The course closes with an applied capstone project where participants build and present a complete, story-driven dashboard to a simulated management audience.

 

Objectives

• Connect to common data sources and shape data using Power Query.
• Build clean, well-structured data models based on star-schema principles.
• Distinguish calculated columns, measures, and calculated tables, and write foundational DAX.
• Apply storytelling principles to structure a dashboard narrative around a clear message.
• Select the chart type and visual format that best match a business question and audience.
• Apply visual design and formatting best practices to reduce clutter and highlight what matters.
• Use interactivity – slicers, bookmarks, buttons, and tooltips – to guide viewers through a dashboard.
• Write advanced DAX, including time intelligence, iterators, and variables.
• Apply advanced modeling techniques, including role-playing dimensions, bridge tables, and row-level security.
• Identify and resolve dashboard performance issues, and publish, share, and govern Power BI reports.
• Write foundational SQL queries – SELECT, WHERE, JOIN, GROUP BY – against a relational database.
• Relate Power BI’s Get Data and query-folding behavior to the SQL running behind the scenes.
• Present dashboards and analytical findings clearly to both technical and non-technical stakeholders.
• Complete an applied capstone project integrating data modeling, DAX, visualization, and storytelling.

 

Target Audience 

• Accounting, finance, and operations professionals who build or maintain recurring dashboards and KPI reports.
• Participants who have completed a foundation-level data analysis course, or have equivalent spreadsheet and reporting experience.
• Anyone responsible for presenting data-driven insights to management or non-technical audiences.
• Power BI developers and BI analysts who want to strengthen core and advanced dashboarding skills.
• Reporting and data analysts who currently build reports in Excel and are transitioning to Power BI.

 

Prerequisites 

• Basic familiarity with Microsoft Excel, including formulas, tables, and simple PivotTables.
• A laptop with Power BI Desktop installed (latest version recommended).
• No prior DAX or SQL experience is required; both are introduced from the ground up.
• A sample or anonymized organizational dataset is helpful for the capstone project, subject to company confidentiality requirements.

 

Course Outline

Day 1 – Core Skills Foundations

Module 1: Power BI Ecosystem Overview 

• Power BI Desktop vs. Power BI Service vs. Power BI Mobile.
• Understanding the data flow: Get Data, Transform, Model, Visualize, Publish.
• Licensing basics (Free, Pro, Premium) – enough to explain sharing later in the course.

Module 2: Connecting to Data

• Common data sources: Excel, CSV, SQL Server, Web, Folder.
• Import vs. DirectQuery vs. Live Connection, and when to use each.
• Query folding basics and why it matters for performance.

Module 3: Power Query – Shaping and Cleaning Data 

• The Power Query Editor interface and Applied Steps.
• Cleaning data: removing duplicates, changing data types, splitting and merging columns.
• Shaping data: unpivot and pivot, group by, merge and append queries.
• Best practice: transform in Power Query rather than in DAX when possible.

 Module 4: Data Modeling Basics

• Star schema vs. snowflake schema.
• Fact tables vs. dimension tables.
• Relationships: cardinality and cross-filter direction.
• Building a clean model from raw tables.

Module 5: Introduction to DAX

• Calculated columns vs. measures vs. calculated tables.
• Core functions: SUM, AVERAGE, COUNTROWS, DISTINCTCOUNT.
• Row context vs. filter context, introduced conceptually.
• CALCULATE as the gateway function.

      Day 1 workshop: Import a raw business dataset, clean it in Power Query, build a star-schema model, and create five basic DAX measures.

 

Day 2 – Storytelling, Communication, and Visualization Tools

Module 6: Data Storytelling Principles

• The narrative arc: context, insight, so-what, and call to action.
• Identifying the audience – executive, operational, or analyst – and adjusting depth accordingly.
• One insight per visual, and avoiding chart clutter.

 Module 7: Choosing the Right Visual

• Matching the visual to the question: comparison, trend, composition, relationship, distribution.
• When not to use pie charts, gauges, or 3D visuals.
• Table vs. matrix vs. card – when each communicates better than a chart.

 Module 8: Visual Design and Formatting

• Color theory for dashboards: sequential, diverging, and categorical palettes.
• Typography and visual hierarchy – titles, subtitles, and labels.
• Alignment, whitespace, and the five-second test.
• Conditional formatting and data bars for emphasis.

 Module 9: Interactivity as a Storytelling Tool

• Slicers, filters, and drill-through used to guide rather than overwhelm the viewer.
• Bookmarks and buttons to build a guided, report-as-a-story experience.
• Tooltips, including custom report-page tooltips, for layered detail.

 Module 10: Communicating Findings to Stakeholders

• Structuring an executive summary page.
• Presenting a dashboard live: talking through insights rather than features.
• Common pitfalls: too many KPIs on one page, mismatched chart types, misleading axes.

      Day 2 workshop: Redesign an unpolished dashboard by applying storytelling and visual design principles, then present a before-and-after with the reasoning behind each change.

 

Day 3 – Advanced Dashboarding with Power BI

Module 11: Advanced DAX

• Filter context deep dive: ALL, ALLEXCEPT, ALLSELECTED, REMOVEFILTERS.
• Time intelligence: TOTALYTD, SAMEPERIODLASTYEAR, DATEADD, and custom calendar tables.
• Iterators (SUMX, AVERAGEX, RANKX) and variables (VAR/RETURN) for readable, debuggable DAX.
• SELECTEDVALUE and dynamic measure and title patterns.

 Module 12: Advanced Data Modeling and Row-Level Security

• Role-playing dimensions, such as Order Date vs. Ship Date.
• Bridge tables for many-to-many relationships, and composite models.
• Row-Level Security – static and dynamic – and testing it with View As Role.

Module 13: Performance Optimization

• Using Performance Analyzer to find slow visuals and DAX.
• Reducing model size: removing unused columns, disabling auto date and time.
• Star-schema discipline and column cardinality as performance levers.

 

Module 14: Advanced Visualization Techniques

 

• Field parameters and what-if parameters for dynamic dashboards.
• Small multiples, custom visuals from AppSource, and drill-through pages.

 Module 15: Deployment and Governance

• Publishing to Power BI Service, workspaces, and apps.
• Dataset refresh scheduling and gateways for on-premises sources.
• Sharing, permissions, and an overview of deployment pipelines.

Day 3 workshop: Build a multi-page dashboard with role-level security, time-intelligence measures, drill-through, and at least one measured performance optimization, then publish it to a workspace.

 

Day 4 – Basic SQL for Power BI Developers and Capstone

Module 16: SQL Fundamentals

• SELECT, FROM, WHERE, and ORDER BY.
• Filtering with AND, OR, IN, BETWEEN, and LIKE.
• Sorting and limiting results (TOP or LIMIT).

 Module 17: Aggregation and Joins

• GROUP BY, HAVING, and aggregate functions (COUNT, SUM, AVG, MIN, MAX).
• INNER JOIN, LEFT JOIN, and RIGHT JOIN, with visual diagrams.
• Mapping joins to Power BI relationships, joining fact and dimension tables.

 Module 18: Writing Queries for Power BI

• Using a SQL query directly in Get Data (native query) vs. letting Power Query build the SQL.
• Understanding which Power Query steps fold to SQL vs. run locally.
• Common Table Expressions (WITH) and SQL views for readability and simpler Power BI models.

 Module 19: Applied Capstone and Presentation

• Pull data using SQL, model it, and build advanced DAX measures.
• Design a polished, story-driven dashboard applying visualization and interactivity principles.
• Identify key findings, business implications, and recommended actions.
• Deliver a concise presentation adapted to a management audience, with trainer and peer feedback.

Day 4 workshop: Given a normalized SQL database, write queries to answer five business questions, recreate the same answers as Power BI measures, then complete and present the capstone dashboard.