Summary  
This chapter explains the difference between DAX calculated columns—which compute and store a value for each row in a table—and DAX measures—which compute and aggregated result on demand within a filter context—and provides guidance on when to use each for performance and modeling.  

General domain of usage  
Business intelligence

DAX offers two types of calculations inside Power Pivot: measures, which live in the calculation area, and calculated columns, which live inside a table. Both use DAX syntax and both are stored in the data model rather than in the Excel workbook.

Evaluates once per row. Each row gets its own independent result based on the values in that specific row. The result is stored in the model like any other column and can be used as a row label, slicer, or column header in a pivot table.

Evaluates once for the entire current filter context — the set of rows currently visible. Returns one aggregated result — a total, a count, an average — that responds to slicers and pivot table filters.

Does the calculation produce a label or category that belongs to a specific row?

Does it produce a total, count, or average that summarises a set of rows?

### The Calculated Column Example
Let's build a Price Band column that assigns each product a label — Low, Mid, or High — based on its unit price. This is a row-level label: every product has its own price band determined by its own unit price. 

```= IF(Products[Unit Price] < 100, "Low", IF(Products[Unit Price] < 500, "Mid", "High"))```

Key Points:
- **No measure name or `:=`** —	calculated columns start with `=` like an Excel formula. The column name is set by renaming the **header** after the formula is entered;
- **Column reference syntax** —	`Products[Unit Price]` — the same table and column syntax used in DAX measures. No cell addresses;
- **Two closing brackets** — one bracket closes the inner IF, one closes the outer. A common source of formula errors.



DAX does not have an `IFS` function — only `IF`. When more than two outcomes are needed, IF functions must be nested, with each false branch leading into the next condition.

Note

## Task
**Step 1 — Add two calculated columns**

1. Open the workbook. Go to **Power Pivot → Manage → Data View**;
2. Calculated column 1 — `Order Size` (Sales table); 
3. Click the Sales tab. Add a calculated column at the far right of the table using the following formula: 

   `= IF(Sales[Quantity] >= 4, "Large", "Small")
`

4. Rename the column `Order Size`;
5. Scroll through the column and confirm that rows with Quantity of `4` or more show `Large` and rows with Quantity of `3` or fewer show `Small`; 

6. Calculated column 2 — `Customer Tier` (Customers table); 
7. Click the `Customers` tab. Add a calculated column using the following formula: 

   `
= IF(Customers[Segment] = "Enterprise", "Tier 1", IF(Customers[Segment] = "SMB", "Tier 2", "Tier 3"))
`
8. Rename the column `Customer Tier`; 
9. Scroll through the column and confirm that `Enterprise` customers show `Tier 1`, `SMB` customers show `Tier 2`, and `Startup` customers show `Tier 3`. 

Which of the following is the most accurate statement about the storage and performance implications of calculated columns versus measures? 

Learn how to turn raw Excel data into a connected data model with Power Pivot, DAX measures, and an interactive dashboard that updates automatically. Starting from a flat table, you will build relationships between multiple tables, write calculated metrics, and deliver a polished, reusable report — all inside Excel.
Suitable for Excel users with basic experience who want to move beyond flat-sheet reporting.

An introduction to what data modeling is, why it matters, and what you will build throughout the course. You will meet the Nordic Bikes project and see the finished dashboard before writing a single formula.

Before building a model, your data needs the right structure. This section covers how to split flat data into clean, purpose-built tables with proper keys, consistent formatting, and clear separation between facts and dimensions.

The core technical section of the course. You will enable Power Pivot, load your tables into the data model, connect them with relationships, and learn how to spot and fix the problems that break a model silently.

Learn to write calculations that go far beyond what Excel formulas can do alone. From basic KPI measures to time intelligence functions, this section builds the analytical layer that powers your reporting.

Turn your model into a finished product. You will build pivot tables that answer real business questions, convert them into charts, and assemble everything into an interactive dashboard controlled by shared slicers.

A structured review of what makes a model reliable, clear, and ready to hand over. The section closes with a capstone project where you apply every skill from the course end to end.

Calculated Columns vs. Measures

The Calculated Column Example

Task