Webbo3 Power BI · Cohort 1 · Start Here
Start Here: Syllabus, Datasets and How This Course Works
Three weeks, sixteen days, one business you will know inside out, and two more you will prove yourself on.
By the end of today you can
- Say who Webbo Oil is, what went wrong, and the five questions your dashboard must answer
- Say what you will build each week, and when every assignment and project is due
- Download the Webbo Oil workbook and know what is in each sheet
- Install Power BI Desktop and set it up the way this course expects
- Read a lesson: the click paths, the formula boxes and the results you check yourself against
Power BI is the tool a business uses to turn a pile of spreadsheets into one page a manager can read in thirty seconds. This course teaches you to build that page from the pile, properly.
You spend the three weeks on one company, Webbo Oil Stations Ltd. Every day adds a layer: first you get its data in, then you clean it, then you model it, then you measure it, and finally you turn it into a dashboard its Managing Director can use. In Week 3 you prove it twice more: alone on PayLink Nigeria, and with your pod on Jade Hotels & Resorts.
1. The Client: Webbo Oil Stations Ltd
The Company
Webbo Oil Stations Ltd started in 2013 with one filling station in Sabon Gari, Kano. It has since grown to 7 stations across Lagos (Ikeja and Lekki), Abuja, Port Harcourt, Ibadan, Kano and Enugu. It sells petrol, diesel, kerosene, engine oil and grease, and employs around 17 station attendants across all its locations.
The company has never had a proper reporting system. Each station manager keeps a logbook and types up a weekly summary in whatever format they are used to. Someone in Head Office pastes these into one long spreadsheet at month end. Nobody has ever built a dashboard from it.
The Business Problem
In June 2023 the government removed the fuel subsidy. In Webbo Oil's own sales, petrol went from about ₦185 a litre in May 2023 to ₦491 in June, almost overnight, and kept climbing to ₦899 by December 2024. The Managing Director, Alhaji Musa Bello, has a business that looks the same on paper (still 7 stations, still selling fuel), but he has no idea whether it is healthier or weaker than before.
He has also pushed his stations for two years to sell more engine oil and grease alongside fuel, on the theory that a customer already at the pump is an easy upsell. Nobody has ever checked whether that strategy is working.
The Brief, in His Own Words
"I have 7 stations and I still run this business by phone calls and gut feeling. Fuel price has tripled since the subsidy went. I need to know which of my stations are actually making money for me and which ones are dead weight. I need to know if this oil and grease push I've been shouting about for two years did anything at all. And I want a dashboard on my phone, not another spreadsheet nobody opens. Build me something I can actually use to make decisions."
The Five Questions Your Dashboard Must Answer
- Which stations bring in the most revenue, and which are falling short of their target?
- What happened to sales volume and revenue around the June 2023 price jump? Did people buy less fuel when the price rose, or keep buying the same amount at a higher cost?
- Fuel or lubricants: which product line actually carries the business? Was the upsell push worth it?
- Do stations differ in how customers pay (cash, POS, transfer), and does that matter for the business?
- How does 2024 compare with 2023, station by station and month by month?
Why the Data Looks Like This
The workbook you are given is exactly what Head Office receives. Seven different station managers type these logs, so station names appear in different capitals and spacing. Dates are typed however each manager's phone or computer defaults to, so there are three different date formats in the same column. A few rows are duplicated because a manager submitted the same log twice by mistake. Some attendant names are missing because those pumps run unmanned or self-service.
This is not difficulty added to make the course hard. It is what real business data looks like before an analyst touches it. Cleaning it properly is the job, not a warm-up before the job.
Your Deliverable
| What | Detail |
|---|---|
| Power BI dashboard | Built from the cleaned, modelled data, covering the five questions above |
| Short insight write-up | 3 to 5 key findings, in plain language the Managing Director can act on |
| Presentation | Presented as if Alhaji Musa Bello himself is in the room |
Picture a Managing Director who has run seven stations on gut feeling for years, opening one page on his phone and finally seeing which ones pay.
2. The Syllabus
Week 1: Getting Data In and Cleaning It
| Day | What you learn |
|---|---|
| Day 1 | Power BI Desktop interface. Connecting to data (Get Data, Navigator) |
| Day 2 | Power Query Editor overview. Data cleaning in Power Query |
| Day 3 | Data transformation in Power Query |
| Day 4 | Lab: clean Sales_2023 together, fix mistakes as a class |
| Day 5 | Appending and merging queries |
Week 2: Modelling and DAX
| Day | What you learn |
|---|---|
| Day 6 | Lab: Append and Merge together. Loading data to the model. What is a data model |
| Day 7 | Star schema. Creating relationships |
| Day 8 | Calculated columns vs measures. DAX basics |
| Day 9 | Lab: build relationships in Model view. Write first DAX measures |
| Day 10 | CALCULATE |
Week 3: Time, Visuals and Delivery
| Day | What you learn |
|---|---|
| Day 11 | Lab: CALCULATE together. Solo Project released: PayLink Nigeria |
| Day 12 | Time intelligence. Solo Project work continues |
| Day 13 | Building visuals |
| Day 14 | Solo Project due. Lab: time intelligence and visuals together. Pod Project released: Jade Hotels |
| Day 15 | Slicers and drill-through. Dashboard layout and storytelling. Pod work |
| Day 16 | Pod presentations |
Assignments and Projects
| Item | Released | Due | What it is |
|---|---|---|---|
| Assignment 1 | Day 4 | Day 6 | Clean Sales_2024 on your own, using the steps built on Sales_2023 |
| Assignment 2 | Day 9 | Day 11 | Build the full Webbo Oil star schema and explain the fact table |
| Assignment 3 | Day 13 | Day 15 | A one-page Webbo Oil dashboard: KPI card, bar chart, trend line, slicer |
| Solo Project | Day 11 | Day 14 | PayLink Nigeria: clean, model, measure and dashboard, alone |
| Pod Project | Day 14 | Day 16 (presented) | Jade Hotels & Resorts as a team: full pipeline, festive season analysis, channel commission breakdown |
Every assignment and project has a lesson of its own in this course, placed straight after the day it is released, with the full brief, the hand-in and how it is marked.
3. The Datasets
Definition
A dataset here is the set of tables that together describe one business. Webbo Oil's arrives as one Excel workbook with a sheet per table.
| Dataset | The business | Used for |
|---|---|---|
| Webbo Oil Stations Ltd | 7 filling stations selling petrol, diesel, kerosene, engine oil and grease, 2023 and 2024 | Live teaching, all three weeks |
| PayLink Nigeria | A mobile money network of 41 agents in 10 states: deposits, withdrawals, airtime, bills and transfers | Solo Project, released Day 11 |
| Jade Hotels & Resorts | Five hotels and resorts taking bookings through six channels | Pod Project, released Day 14 |
Download Webbo Oil now. The other two are on their project pages, released on the day the project starts.
Webbo Oil Stations Ltd
Download all as one zip file (webbo-oil-stations.zip)
- PowerBI_WebboOil_Stations.xlsx : every sheet in one workbook, exactly as Head Office sends it
Save it in a folder you will not move, such as Documents\Webbo3 Power BI\webbo-oil. Power BI remembers the full path to the file, so moving it later breaks your report until you point it at the new place.
What Is in Each Sheet
| Sheet | What it holds |
|---|---|
| Cover | A title page: company details and a list of the sheets |
| Sales_2023 | Raw daily sales log, all 7 stations, 2023 |
| Sales_2024 | Raw daily sales log, all 7 stations, 2024 |
| Station_Master | Station names, city and region |
| Product_Master | Product list: fuels and lubricants |
| Attendant_Directory | Staff list with contact and hire details |
| Station_Targets | A revenue target per station |
Already you can see the problems this course fixes: names in capitals and with extra spaces, dates written three ways, and empty attendant names. Each one has a lesson.
Picture seven station managers each keeping their own notebook, in their own handwriting, for two years. Your job is to turn those notebooks into one reliable page.
4. Setting Up Power BI Desktop
Definition
Power BI Desktop is free and runs on Windows only. There is a web version (Power BI Service) for sharing reports, but the cleaning and modelling you learn here happen in Desktop.
Install it
- Use the Microsoft Store version. It updates itself every month, so your screen matches the class.
- On a Mac? Power BI Desktop does not run on macOS. Use a Windows laptop, or Windows in Parallels. Tell your tutor on Day 1, not on Day 4.
- 8 GB of memory is comfortable. It will run on 4 GB, slowly, with nothing else open.
One Setting to Check on Day 1
Some of Webbo Oil's dates are written day first (13/10/2023), the Nigerian and British way. Power BI reads dates with your computer's regional setting, and many laptops are set to the United States, where the month comes first. You will learn to handle this properly on Day 2; for now, check the setting so you know what you have:
Check your locale
Install Power BI Desktop, open a blank report, and find the Regional Settings page above. Write down what it says. If it says English (United States), you will meet the date problem on Day 2, and that is exactly what we want.
5. How to Read Each Lesson
Every lesson follows the same pattern, so you always know where you are:
- Definition, then a real-life example, then the types, before anything is clicked or typed.
- Click paths in grey boxes with a yellow edge: the exact buttons to press, in order. All of Power Query is done this way: you never type code to clean data.
- Formula boxes in dark editors, from Week 2: the DAX measures you type in the formula bar, with every step commented, and a "What this code does" strip above each one.
- Result panes underneath: the preview grid, card or chart that the step produces on the workbook.
Every number in a result pane is calculated from the same workbook you downloaded, using the same steps. If your number is different, you have not found a Power BI bug: one of your steps differs from the lesson. Go back through Applied Steps until the row counts match.
6. How Work Is Handed In
- Hand-ins are links, not uploads. Save your .pbix file and screenshots to Google Drive, set sharing to "Anyone with the link can view", and paste the link on the assignment.
- You can edit a hand-in until a tutor marks it.
- Late work is marked, with the deadline on the page. Missing work is not.
- Name every file with your name and the task:
Chidinma_Okafor_Assignment1.pbix.
Do This Now
- Read the brief in section 1 twice, and write the five questions at the top of your notebook.
- Install Power BI Desktop from the Microsoft Store.
- Download the Webbo Oil workbook into a folder you will not move.
- Open it in Excel and find three problems in the Sales_2023 sheet yourself.
- Check your locale setting and write it down.
- Create a Google Drive folder for your hand-ins.
Tick Before You Move On
- ☐ I can say what Alhaji Musa Bello wants to know, in my own words
- ☐ Power BI Desktop opens on my laptop
- ☐ The Webbo Oil workbook is saved in a folder I will not move
- ☐ I know when all three assignments and both projects are due
- ☐ I know my Power BI locale setting
Quick Recap
Webbo Oil has 7 stations, two years of messy sales, and a Managing Director with five questions. Power BI connects, cleans, models and reports, in that order. PayLink Nigeria is your solo proof; Jade Hotels is your team's. Result panes are your answer key: match the row counts and the numbers. Hand-ins are links to Google Drive, editable until marked.
Final Scenario
Three weeks from now, Alhaji Musa Bello opens your dashboard on his phone and asks, "So which of my stations are dead weight, and did the oil and grease push do anything?"
You answer from a page you built from the raw workbook, and you can explain every number on it, down to the step in Power Query that made it right.
That is where this starts. Day 1 is opening the program and getting the data in.
Next, Day 1: the Power BI Desktop interface, and connecting to the Webbo Oil workbook with Get Data and the Navigator.