Power BI Video Guide: From First Report to Defensible Decision

Choose one course to build with

Do not try to complete all five. Pick the course that matches your available time and starting point, then make one small report from start to finish. The other videos are useful alternatives or refreshers when you need a different pace.

Power BI Beginner to Pro 2026 Edition: Full Hands-On Tutorial

Pragmatic Works • 3 hours 28 minutes

Best if: you want a full hands-on introduction and enough time to see data preparation, modeling, and report construction in one sitting.

Learn Power BI in Under 3 Hours: Formatting, Visualizations, Dashboards + Full Project

Alex The Analyst • 2 hours 5 minutes

Best if: you learn by completing a project and want formatting and visuals in the same practical walkthrough.

How I Would Learn Power BI Fast If I Could Start Over

Mo Chen • 8 minutes 35 seconds

Best if: you need a short orientation before choosing a longer course, especially for modeling, DAX, and project work.

Learn Power BI Fast: Full Beginner Crash Course

Data with Baraa • 45 minutes 54 seconds

Best if: you want a compact first pass before slowing down with the book, a dataset, and a more deliberate report.

Beginner to Pro Data Analysis with Power BI: Full-Length Course

Chandoo • 42 minutes 50 seconds

Best if: you want another concise project-oriented path after you have completed one primary course.

Learn just enough DAX to check a measure

You do not need to become a DAX developer to use this book or build a defensible report. You do need to read a measure closely enough to ask what it aggregates, which filters it applies, what grain it returns, and whether that definition matches the business claim you are about to make.

Start with the first primer after your Power BI orientation and before Chapter 9’s wrong-measure practice. Stop when you can inspect a simple measure and explain why two fields both labeled revenue might return different totals. The second video is an optional Chapter 9 follow-up for understanding why filter context changes a measure. Advanced time intelligence, iterator patterns, and debugging can wait until your work requires them.

Measures vs. calculated columns in DAX and Power BI

SQLBI • 6 minutes

Start here if: you need to distinguish a row-level column from a context-sensitive measure before you inspect a result or trust its label. Use it for measure literacy, not as a prerequisite to learn advanced DAX.

Introducing CALCULATE in DAX

SQLBI • 13 minutes 57 seconds

Optional Chapter 9 follow-up: learn why filter context can make two plausible measures return different totals. Watch after you have practiced naming the measure and grain behind a Copilot-generated claim.

Build more than a dashboard

The point of the first report is not to collect visuals. It is to practice the chain of decisions that makes a report useful and reviewable.

1. Start with the decision

   Write one question before opening Power BI: for example, Which product group needs attention this quarter, and compared with what? The question tells you what data, measure, and comparison belong in the report. Without it, a report can be busy and still say nothing.

2. Make the data trustworthy enough to use

   Use Power Query to inspect missing values, inconsistent labels, and the joins that turn separate files into an analyzable dataset. Keep the transformations visible. A clean-looking visual cannot repair a weak data foundation.

3. Model the relationships before writing the story

   Separate the events you measure from the categories you use to explain them. Then test whether filtering a category produces the result you expect. Measures become easier to reason about when the model has a clear shape.

4. Choose a form that makes the comparison legible

   Use a chart because its form answers the question, not because the visual looks impressive. A bar chart, line chart, table, or KPI card each makes a different claim easy to read. The Chapter 4 companion and the Chart Gallery are the places to test that choice.

5. Read the result as an argument, not decoration

   Before sharing, ask what comparison the reader will see first, what context is absent, and whether the visual supports the conclusion you are about to make. The report is ready when another person can trace the claim back to the measure, the comparison, and the data.

A first-project learning path

Work through this sequence with one small dataset and one decision question. Each linked segment is a place to begin; pause the video to make the same choice in your own report before moving on.

1. Set the scope before you touch the canvas

   Watch: Chandoo at 0:39 previews the components of a first Power BI project: data cleanup, modeling, introductory DAX, and visuals. Mo Chen at 0:36 frames the destination as a project you can present, not a collection of isolated features.

   Do: write a one-sentence decision question, name the audience, and choose one measure that would help that audience act. Keep the project narrow enough to finish.

2. Bring in the data and inspect it before reporting

   Watch: Alex The Analyst at 2:59 shows the choice between loading a selected sheet and opening Transform Data. The following 3:11 segment positions the Power Query Editor as the place to prepare data for visualizations.

   Do: list the fields you need to answer the question and identify at least one check for type, missing values, duplicated rows, or inconsistent labels before you load the model.

3. Clean and reshape the data where the work remains visible

   Watch: Chandoo at 11:39 opens Power Query from Transform Data and demonstrates it as the processing layer for cleaning and reshaping. For a second explanation of why this step matters, Pragmatic Works at 8:02 introduces data cleansing as a core Power BI process.

   Do: make a short set of intentional transformations, then describe each one in business language. If you cannot explain why a step exists, remove it or investigate it before continuing.

4. Shape a model that matches the question

   Watch: Pragmatic Works at 9:07 moves from cleanup to combining multiple sources in the modeling phase. Mo Chen at 3:48 recommends separating fact and dimension tables and connecting them correctly before leaning on measures.

   Do: identify the event or transaction table, the categories that explain it, and the relationships between them. Test one filter from each category before creating a report page.

5. Create measures that answer a defined comparison

   Watch: Chandoo at 18:14 introduces a new measure and the DAX formula bar. Alex The Analyst at 32:27 connects related product fields to measures and columns, and 35:14 works through a simple aggregate.

   Do: start with one measure such as total sales, count of cases, or average response time. Compare it with a baseline: prior period, target, category, or plan. A number by itself is not yet a finding.

6. Build the visual around a dimension and a measure

   Watch: Data with Baraa at 25:15 builds a bar chart by pairing a product dimension with a total-sales measure. The 29:22 segment extends the same thinking to a time-based comparison by pairing a date with the measure.

   Do: build one comparison chart and one time or context view only if they answer different parts of the question. Use the Chart Gallery and Chapter 4 companion to challenge the form before you format it.

7. Finish with a report you can explain and defend

   Watch: Chandoo at 41:36 closes by separating the jobs of Power Query, DAX and Power Pivot, and the visual layer. That separation is useful when a report is not working: diagnose the data, logic, or presentation rather than adjusting the chart at random.

   Do: explain your final report to someone else: the decision, the measure, the comparison, the data boundary, and one limitation. Then use the Practice hub to keep building the judgment that turns a working report into a defensible one.

Continue on this site

Use Power BI to choose the right Power BI and Fabric account path. Use the teaching datasets when you need a scenario designed for practice rather than a generic sample file. Use the Practice hub when you want to test the reasoning behind a report, not merely reproduce its clicks.