- Home > Get Data > Text/CSV.
- Load customers.csv, products.csv, orders.csv, and order-details.csv from the Northwind folder.
- Call out the Fields pane and explain data type icons.
Tip: Show how to rename report pages to "Overview" and "Model Check".
Build and Explain Your First Report Page
This session teaches learners how to load data, build visuals, choose the right chart for a question, and connect tables in Model view. It is designed for people who are brand new to data modelling.
Prerequisite reminder: learners should finish the "Introduction to Power BI" module from the overview page before this session starts.
Session Agenda (2 Hours)
| Time | Topic | Outcome |
|---|---|---|
| 00:00 - 00:20 | Power BI interface walkthrough | Learners identify Report, Data, and Model views |
| 00:20 - 01:10 | Visualisation demos | Learners can create and format key chart types |
| 01:10 - 01:15 | Break | Quick reset |
| 01:15 - 01:50 | Data modelling in Model view | Learners create one-to-many relationships |
| 01:50 - 02:00 | Recap and Q&A | Learners are ready for DAX + Power Query |
How to Demo Creating Visualisations
Use the accordion below during delivery. Keep one panel open at a time to avoid overwhelming absolute beginners.
- Create a clustered column chart: Axis = categories[categoryName], Values = order-details[quantity].
- Create a card: Count of orders[orderID].
- Create a line chart: X-axis = orders[orderDate], Values = order-details[quantity].
- Create a matrix: Rows = customers[country], Columns = categories[categoryName], Values = order-details[quantity].
- Enable titles and data labels for readability.
- Apply consistent colors using the Power BI yellow accent sparingly.
- Add a Region slicer and click values to show cross-filtering.
- Use the visual menu (...) to sort by quantity descending.
When to Use Each Visual (and Why)
- Bar / Column chart: best for comparing categories.
- Clustered bar: use with long labels or ranking charts.
- Avoid: pie charts when you need precise comparisons.
- Line chart: best for order/sales patterns over time.
- Area chart: good when emphasizing overall volume.
- Avoid: using trend charts without a time-based axis.
- Donut chart: only when there are 2-5 categories.
- Stacked charts: compare total + category contribution together.
- Avoid: too many slices; switch to bars for clarity.
- Card: one KPI headline value.
- Table: row-level detail for audits.
- Matrix: pivot-style summary by two dimensions.
Data Modelling and the Table / Model View
- Open Model view and place customers, products, orders, and order-details near each other.
- Create customers[customerID] → orders[customerID].
- Create products[productID] → order-details[productID].
- Create orders[orderID] → order-details[orderID].
- Confirm cardinality is one-to-many in all links.
- Dimension tables (customers, products) provide descriptors.
- Fact tables (orders, order-details) store transactions.
- Selecting a customer should filter related orders automatically.
Simple language: one customer can have many orders; one product can appear in many order line items.
- Data type mismatch between keys (text vs number).
- Trying to relate on messy text without cleaning first.
- Using ambiguous many-to-many links in beginner models.
Instructor note: keep this practical. Create one visual using fields from Customers + Orders + Products to prove the relationships are working live.