STA191Data Visualization
Topic 5 · Power BI  ›  Week 9

Power BI — Getting Started

New tool, same thinking. Everything you learned about choosing charts still applies — you're just building them in Microsoft Power BI now, which handles bigger data and produces the interactive dashboards your presentation task asks for.

By the end of this week you can…

  • Explain the difference between Power BI Desktop and Power BI Service.
  • Install Power BI Desktop and sign in with your UiTM student email.
  • Import an Excel file and clean it in Power Query before loading.
  • Build and format a pie chart and a scatter plot, including a trendline.
  • Share your work without a Pro licence.
Datasets: 📘 Examples — budget & cars 📝 Practice — clubs & health

9.1  What Power BI is

Microsoft Power BI is a business-intelligence platform for analysing, visualising and sharing data. You connect it to one or more sources, transform and clean the information into a structured model, then present it through interactive charts and graphs.

VersionWhat it's forWhere it runsCost
Power BI DesktopBuilding and designing reports — this is what you'll use all semesterInstalled on your computerFree
Power BI ServicePublishing, viewing, sharing and collaboratingIn the cloudRequires a Pro licence
● Before the lab — install it

Download Power BI Desktop from microsoft.com/power-bi/desktop and install it before class. Sign in with your UiTM student email. This gives you a basic account — not a Pro licence, which is all you need for this course.

On a Mac? Power BI Desktop is Windows-only. Use a lab PC, or run Windows through Boot Camp, Parallels or a virtual machine. Sort this out early — don't discover it in the lab.

9.2  Import your data

  1. Open Power BI Desktop. When asked whether to import data or start fresh, choose Start with a blank report.
  2. Home ▸ Get data ▸ Excel workbook → choose Week 9 Examples (Budget & Cars).
  3. In the Navigator window, tick the worksheets you want — select all sheets for this exercise.
  4. Click Load to import as-is, or Transform Data to clean it first.

9.3  Power Query — clean before you load

Transform Data opens Power Query, where you prepare data before it reaches your report. It's the Power BI equivalent of the cleaning you did by hand in Week 5 — except every step is recorded and repeatable.

Common transformWhat it fixes
Use first row as headersColumn names imported as data.
Change typeNumbers or dates that arrived as text and won't chart properly.
Remove columns / rowsFields you don't need, or blank rows at the top.
Remove duplicatesRepeated records inflating your totals.
Replace valuesInconsistent spellings — the “Selangor / SELANGOR / Selangorr” problem from Week 5.
Split columnTwo pieces of information stuck in one field.
  1. Make your edits in Power Query — each one appears in Applied Steps on the right.
  2. Click Close & Apply to send the cleaned data into your report.
Applied Steps is your undo history. Made a mistake three steps ago? Delete that step instead of starting over. This is why cleaning in Power Query beats cleaning by hand — the recipe is saved, so refreshing the source re-runs it automatically.

9.4  Finding your way around

Three panels do most of the work, and you'll use them in this order every single time:

Data

Your tables and fields. Tick a field here to start a visual — Power BI makes a first guess at the chart type.

Visualizations

The chart gallery. Click an icon to change type, and drag fields into the wells (X-axis, Y-axis, Legend, Values).

Format visual

The paintbrush icon. Titles, legends, data labels, colours, gridlines — everything from Chapter 2 lives here.

● Session 1 recap

Desktop to build (free), Service to publish (Pro). Get data → clean it in Power Query → Close & Apply. Then: tick fields in Data, pick the chart in Visualizations, tidy it in Format visual.

9.5  Example 1 — pie chart, household budget

The situation. A family wants to understand how their monthly budget is split across expense categories. They've recorded a month of spending and want to see the percentage going to each category.

Use the Example 1 Pie Chart sheet — two columns, Category and Amount (RM).

  1. In the Data panel, tick both fields.
  2. In Visualizations, choose the Pie chart.
  3. Open Format visual and set:
    • Legend → Position: Top centre
    • Data labels → Position: Inside; Overflow: Off
    • Data labels ▸ Values → Display units: None
    • General ▸ Title → “Total Expense by Category”, font size 20
Expected result — total expense by category
  • Rent — 37.0%
  • Groceries — 24.7%
  • Transport — 13.8%
  • Utilities — 12.3%
  • Entertainment — 9.3%
  • Other — 3.0%

Rent alone takes over a third of the budget. Percentages are exactly why a pie works here — six parts of one whole. Your own figures will differ slightly depending on the file.

● Remember Chapter 2

A pie is only appropriate because this is parts of one whole with few categories. Had there been fifteen expense types, a horizontal bar chart would win. The tool changed this week; the judgement didn't.

9.6  Example 2 — scatter plot, engine size vs fuel efficiency

The situation. An automotive researcher wants to know whether larger engines (litres) go with lower fuel efficiency (miles per gallon). A scatter plot shows the relationship between two numeric variables.

Use the Example 2 Scatter Plot sheet — Car Model, Engine Size (L), Fuel Efficiency (MPG).

  1. Select the dataset in the Data panel and include all variables.
  2. In Visualizations, choose the Scatter chart.
  3. Set X-axis = Engine Size (L), Y-axis = Fuel Efficiency (MPG).
  4. Title it “Engine Size vs. Fuel Efficiency” and remove the gridlines.
  5. Open the Analytics pane (the magnifying-glass icon) → add a solid Trend line.
Expected result — a clear negative relationship
Engine size (litres) → MPG → trendline

A negative correlation: as engine size increases, fuel efficiency falls. The trendline makes the direction unmistakable — but remember, it shows association, not proof of cause.

9.7  Sharing without a Pro licence

Publishing to Power BI Service needs a Pro licence you don't have. The way around it is OneDrive.

  1. Sign in to OneDrive with your UiTM account.
  2. In Power BI, finish your visuals, then click Share.
  3. Choose Save a copy in OneDrive — create a folder, name it clearly, and save the .pbix file.
  4. Copy the link and share it.
Opening someone else's link: easiest is to paste the link, download the file, then open it in your own Power BI Desktop.

9.8  Practice

Both use the Week 9 Practice (Clubs & Health) file. Do them in Power BI Desktop.

● Practice 1 · Pie chart — student clubs

A university wants to see how students are spread across five co-curricular clubs, to help allocate funding.

  • Insert a pie chart from the Practice 1 sheet.
  • Add data labels showing percentage, and a sensible legend.
  • Use contrasting colours for each slice.
  • Emphasise the largest segment with a bolder colour or a border.
  • Title it “Distribution of Student Club Membership”.
● Practice 2 · Scatter plot — exercise and blood pressure

A medical researcher is studying whether weekly exercise hours affect blood pressure in adults.

  • Load the Practice 2 sheet and insert a scatter chart.
  • X-axis → Weekly Exercise (hours); Y-axis → Blood Pressure (mmHg).
  • Title it “Exercise vs. Blood Pressure” and add a trendline.
  • Then answer in words: what relationship does the chart show — and can you conclude that exercise causes lower blood pressure?
● Session 2 recap

Tick the fields, choose the visual, format it properly. Pie for parts of a whole with few categories; scatter for the relationship between two numeric variables, with a trendline from the Analytics pane. Share via OneDrive, not Power BI Service.

Key terms & definitions

Power BI Desktop
The free Windows application used to build and design reports.
Power BI Service
The cloud platform for publishing and sharing; needs a Pro licence.
Power Query
The data-preparation window opened by Transform Data, where cleaning steps are recorded and repeatable.
Applied Steps
The list of every transform you've made, in order — editable and removable at any time.
Close & Apply
Commits your Power Query edits and loads the cleaned data into the report.
Navigator
The window for choosing which worksheets or tables to import from a source file.
Analytics pane
Where you add reference elements to a visual, such as a trendline or average line.
.pbix file
The Power BI report file format — holds your data model, visuals and layout together.

✅ Quick self-check

1. Which version of Power BI do you use to build reports on your own computer, for free?

2. You want to fix inconsistent spellings before the data reaches your report. You click…

3. A trendline is added from which pane?

4. The scatter plot slopes downward from left to right. This shows…

5. Without a Pro licence, the practical way to share your report is…

Week 10 →