So you keep hearing these three names: Power Query, Power Pivot, and Power BI. And because they all start with Power, it sounds like three versions of the same thing.
They are not. Two of them are features that already sit inside your copy of Excel, and one is a separate app altogether.
In this article, I’ll explain what each one does, how the three fit together, and give you a simple way to pick the right one (including an interactive helper that does the picking for you).
Power Query vs Power Pivot vs Power BI: The Short Answer
Here is the one-line version: Power Query gets your data ready, Power Pivot analyzes it inside Excel, and Power BI turns it into dashboards you can share with anyone.
A cleaner way to think about it: Power Query and Power Pivot are features inside Excel. Power BI is a separate product that has its own copy of both built in.
So this is not a three-way contest. You are really answering three small questions:
If that already answers your question, great. If you want to actually understand how the three relate (so you never mix them up again), keep reading.
What is Power Query?
Power Query is the data preparation tool built into Excel. You’ll find it on the Data tab, in the Get & Transform Data group.
Think of it as a smart import wizard. You connect to a source (an Excel file, a folder of CSVs, a database, a web page), then apply cleanup steps such as removing columns, filtering rows, splitting text, merging tables, or unpivoting a wide layout.
Power Query records every step. When the source data changes, you click Refresh and it replays the whole cleanup on the new data automatically.
Behind the scenes, each step writes a line of code in a language called M. You rarely need to touch it. Most transformations are just clicks in the Power Query editor.
If you’re new to it, I have a detailed guide on what Power Query is and how to use it, and a free Power Query course as well.
What is Power Pivot?
Power Pivot is the data modeling engine inside Excel. It manages something called the Data Model, which is an in-memory database that lives behind your workbook.
Why would you want a database behind your workbook? Two reasons.
First, size. A worksheet stops at 1,048,576 rows. The Data Model compresses data heavily and can hold millions of rows while staying fast.
Second, relationships. Instead of writing VLOOKUP or XLOOKUP to pull everything into one giant table, you load Sales, Products, and Customers as separate tables and connect them with relationships. A Pivot Table can then use fields from all of them at once.
Power Pivot also brings its own formula language called DAX. That is where you write measures such as Total Sales or Profit Margin that recalculate as people filter and slice the Pivot Table.
One catch: even though Power Pivot ships with Excel (2016 and later on Windows), its ribbon tab is hidden by default. Go to File > Options > Add-ins, select COM Add-ins in the Manage drop-down, click Go, and check Microsoft Power Pivot for Excel.
What is Power BI?
Power BI is not an Excel feature. It is a separate product from Microsoft, built for creating interactive reports and dashboards and sharing them with other people.
It comes in a few parts. Power BI Desktop is a free Windows app where you build reports. The Power BI Service (powerbi.com) is where you publish them so others can view them in a browser or on their phone.
Here is the part that surprises most Excel users: when you open Power BI Desktop, the data tools inside it are the ones you already know.
Click Transform data, and you are in the Power Query editor. Same interface, same steps, same M language. And the modeling side of Power BI (tables, relationships, DAX measures) is the same engine that powers Power Pivot in Excel.
So Power BI is not a competitor to Power Query or Power Pivot. It is a different home for them, with much stronger visuals and sharing bolted on top.
Power BI Desktop is free to use. To share your reports with others through the Power BI Service, each person generally needs a paid per-user license (Power BI Pro).
How the Three Fit Together
The easiest way to keep the three straight is to follow the journey your data takes. Use the toggle below to see the same journey in Excel and in Power BI:
Notice what the toggle shows. The first three stations are the same in both. Power Query and the Data Model do the same jobs in Excel and in Power BI.
The difference is the last stop. In Excel, your analysis lives in a workbook. In Power BI, it becomes an interactive report that other people open in a browser or on their phone.
That is why the skills transfer so well. Learn Power Query and some DAX in Excel, and you already know most of what Power BI Desktop asks of you.
Power Query vs Power Pivot vs Power BI: Side-by-Side Comparison
Here is the full comparison in one place:
| Power Query | Power Pivot | Power BI | |
|---|---|---|---|
| What it is | A data cleanup feature inside Excel | A data modeling add-in inside Excel | A separate app plus an online service |
| Main job | Import, clean, and reshape data | Store big, related tables and calculate with DAX | Build interactive dashboards and share them |
| Where you find it | Data tab (Get & Transform Data) | Its own ribbon tab, once enabled | Power BI Desktop app + powerbi.com |
| Language | M (written for you as you click) | DAX | Both (M for prep, DAX for calculations) |
| Typical output | Clean tables | Pivot Tables backed by the Data Model | Reports and dashboards |
| Data size | Limited by where you load it | Millions of rows | Millions of rows |
| How you share it | The workbook itself | The workbook itself | Cloud links, apps, and phones |
| Cost | Included with Excel | Included with Excel (Windows) | Free Desktop app, paid license to share |
| Works on Mac? | Yes (Microsoft 365) | No | Browser only |
One row in this table matters more than the rest: how you share it. Power Query and Power Pivot live and die inside a workbook. Power BI exists so the result can live outside one.
Power Query vs Power Pivot: What’s the Difference?
These two get confused the most, because both sit inside Excel and both deal with data.
The split is simple. Power Query works on data before it lands: connecting, cleaning, reshaping, combining. Power Pivot takes over after it lands: storing large related tables and calculating results with DAX.
They are not rivals. They are two stations on the same assembly line, and on real projects you’ll often use both in the same workbook.
If your question is really “should I build this calculation in Power Query or in DAX”, I’ve written a whole article on exactly that: Power Query vs DAX.
Power Query vs Power BI: What’s the Difference?
This one is a bit of a trick question, because Power BI has Power Query inside it.
In Excel, Power Query is the Get & Transform Data group on the Data tab. In Power BI Desktop, the same tool opens when you click Transform data. Same editor, same steps, same M language underneath.
So the real comparison is not Power Query vs Power BI. It is Excel vs Power BI as the home for your finished work. Power Query comes along either way.
If your output is a workbook for you or a small team, Excel with Power Query is enough. If your output is a dashboard a wider audience views and filters, that is Power BI’s job.
Power Pivot vs Power BI: What’s the Difference?
Under the hood, these two are close relatives. Power BI’s data modeling side uses the same engine as Power Pivot, and both speak DAX.
Power Pivot is that engine living inside Excel. Your model feeds Pivot Tables and Pivot Charts, and everything stays in the workbook.
Power BI wraps the same engine in a full reporting product: drag-and-drop visuals, dashboards, scheduled refresh, and sharing through the cloud with per-user access control.
A useful way to decide between them: think about your audience. If the people consuming your analysis live in Excel, stay with Power Pivot. If they expect a link that opens an interactive dashboard, build it in Power BI.
What Do These Tools Cost?
Here is some good news: two of the three cost you nothing extra.
You never buy Power Query or Power Pivot separately. If you have Excel on Windows (2016 or later), you already own both. And since Power BI Desktop ships with its own copies of them built in, they are free on that side too.
A few notes on the Power BI side of that card, since it is the only one where money enters the picture:
- Power BI Desktop is completely free, with no feature limits on building reports. You only pay when you want to share through the Power BI Service.
- Power BI Pro is $14 per user per month (billed yearly) as I write this, and both the person sharing and the people viewing need a license.
- Already on Microsoft 365 E5? Power BI Pro is included in that plan, so your organization may already be paying for it.
- There is also a free Power BI account for the Service, but it only lets you build reports for yourself. Sharing with others is the paid part.
So for most Excel users, the practical answer is: everything in this article is free until the day you need to share interactive dashboards with a team.
Which One Should You Use? (Interactive Tool Picker)
Below is a quick interactive helper. Click the situation that sounds most like yours, and it will tell you which tool to reach for and why:
If your situation isn't listed, use the three questions from the start of this article. Messy data? Power Query. Too big or too connected for normal Excel? Power Pivot. Other people need an interactive dashboard? Power BI.
Clearing Up the Names
Microsoft did not make the naming easy here, so let me untangle the terms you keep seeing together:
| Term | What it actually is |
|---|---|
| Power Query | The data cleanup tool, available in both Excel and Power BI |
| M | The language Power Query writes behind the scenes as you click |
| Get & Transform Data | Power Query's official name on Excel's Data tab |
| Power Pivot | The Excel add-in that manages the Data Model |
| Data Model | The in-memory database behind Excel (and Power BI) that stores tables and relationships |
| DAX | The formula language for calculations in Power Pivot and Power BI |
| Power BI Desktop | The free Windows app where you build Power BI reports |
| Power BI Service | The powerbi.com site where reports get published and shared |
The pattern to remember: green terms are about preparing data, blue terms are about modeling and calculating, and yellow terms are about reporting and sharing.
What Should You Learn First?
If you're starting from scratch, here is the order I recommend.
Start with Power Query. It pays off immediately, it needs zero coding, and every hour you save on manual cleanup keeps paying every week.
Then learn the Data Model and basic DAX through Power Pivot. Begin with relationships and simple measures like SUM and DIVIDE, and grow from there.
Once you know those two, Power BI is a small step, not a leap. Its data side is the same Power Query and DAX you already know. You are really just learning the visuals and the publishing workflow.
Things to Keep in Mind
- Power Pivot's tab is hidden by default. Enable it via File > Options > Add-ins > COM Add-ins, or just click Data > Manage Data Model once, and the tab appears.
- Power Pivot is Windows-only. Excel for Mac supports Power Query (with fewer connectors), but there is no Power Pivot on Mac.
- Power BI Desktop is Windows-only too. Mac users can view and edit reports through the browser at powerbi.com, but the Desktop app itself doesn't run on a Mac.
- You don't need Power BI to benefit from the other two. Plenty of serious analysis ships as an Excel workbook with Power Query and Power Pivot doing the heavy lifting.
- The skills transfer one-to-one. Queries you build in Excel can be copied into Power BI Desktop, and the DAX you learn in Power Pivot works as-is in Power BI.
- A worksheet caps out at 1,048,576 rows. When Power Query loads data to a sheet, that limit applies. Load to the Data Model instead and the ceiling effectively disappears.
- Sharing is where Power BI costs money. Building reports in Power BI Desktop is free. Publishing them so others can view them generally needs a paid per-user license.
In this article, I covered what Power Query, Power Pivot, and Power BI are each built for, how they fit together, and how to pick the right one for your work. I hope you found this article helpful.
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