Why Microsoft changed the name, and why the confusion never really went away
By Hiran de Silva
There is a strange story inside Excel.
It is a story about a tool, but it is also a story about branding, social media, and the way technology gets bent out of shape once marketing momentum takes over.
That story is Power Query.
Because Power Query was called Power Query, then in Excel it was presented as Get & Transform, and today Microsoft’s own documentation still describes it as “Power Query (known as Get & Transform in Excel).” In other words, the underlying technology kept one identity, while the product surface in Excel emphasized another. That alone tells you something important: Microsoft itself has wrestled with how this tool should be understood.
And the reason this matters has come back into focus again with Copilot. A feature that was presented as Agent Mode in late 2025 now appears to have been relabelled Edit with Copilot only a few months later. That is not just a minor naming tweak. It suggests a broader pattern: when a feature starts being interpreted too broadly, too vaguely, or too grandly, Microsoft sometimes steps in and tries to pull the meaning back toward what the feature is actually for.
That is exactly the lens through which Power Query should be examined.
The first thread: what Power Query really is
Historically, Power Query did not come out of nowhere.
Before Power Query, Excel already had external data capability. Microsoft Query still exists in Excel today, though now it sits under legacy import options, and Microsoft’s documentation still describes how it is used to retrieve external data. In earlier generations of Excel, the user-facing idea was straightforward: get external data. Connect to a source, retrieve data, refresh it, and use it in the workbook.
When Power Query arrived, Microsoft did not present it merely as a prettier import wizard. It became a much broader data connectivity and data preparation layer. Microsoft’s own documentation now describes Power Query as a data transformation and data preparation engine, and explicitly says it performs ETL — extract, transform, load. That description matters enormously, because it tells us what category of tool this really is.
So the simplest way to frame the technical history is this:
Get External Data / Microsoft Query was the earlier Excel-era mechanism for connecting to outside data.
Power Query was the newer, broader, more capable generation of that data-acquisition-and-shaping function.
That does not mean it was designed to become “the new Excel.” It means it was designed to improve Excel’s ability to bring in, clean, reshape, and load data.
The second thread: Microsoft branding cycles
There is another story running in parallel, and that is Microsoft’s branding history.
In earlier decades Microsoft loved the prefix Microsoft. Then, in the Windows era, the key marketing idea became Visual: Visual Basic, Visual C++, Visual InterDev, and so on. Later, in the modern data-and-automation era, the marketing prefix became Power: Power Pivot, Power Query, Power Apps, Power Automate, Power BI. This was not random. It was a branding pattern — a way of grouping a new generation of products and making them feel part of a new wave.
Power Query fit beautifully into that pattern.
Technically, it was a stronger data-preparation layer. But commercially and socially, it was also a perfect marketing label. “Power Query” sounds bigger, sexier, more revolutionary than “data import and transformation.” It sounds like a breakthrough category of Excel itself.
That was the gift, and also the problem.
The third thread: social media and the mislabelling of tools
Once you call something Power Query, and once it has a long ribbon full of options, steps, transformations, merges, pivots, unpivots, and mashups, you have created ideal social-media material.
Why?
Because the tool is visually demonstrable. It has many buttons. It produces before-and-after moments. It lends itself to screen recordings. It creates the impression that something powerful and advanced is happening. In social media terms, it is highly marketable.
And that is where the confusion begins.
Because the question is not, “Can Power Query do this?”
The real question is, “What kind of problem was Power Query designed to solve?”
Microsoft’s own description is the clue: data preparation, transformation, and ETL.
That is a very specific category.
An ETL tool is not a universal replacement for every business process, every spreadsheet pattern, every reconciliation idea, every data-entry workflow, or every relational design problem. ETL has a real purpose in systems architecture: move data from sources, reshape it, and load it into a destination or model for use.
But social media does not reward architectural discipline. It rewards novelty, spectacle, and apparent cleverness.
So the narrative drifted.
And what happened next, in my view, is that Power Query was increasingly mislabelled. Not always maliciously. Often enthusiastically. Often innocently. But mislabelled all the same.
It was presented not just as a data-preparation engine, but as a kind of next-generation Excel brain. A replacement for established methods. A substitute for structured database thinking. Sometimes even, astonishingly, as if it made relational databases unnecessary.
That is where the trouble starts.
Why “Get & Transform” makes more sense than “Power Query”
This is why the Excel 2016 ribbon label matters.
When Microsoft built the functionality into Excel 2016, the ribbon section was called Get & Transform. That is not just cosmetic. It is descriptive. It tells the user what the feature is for: get data, then transform data.
In other words, it nudges the user back toward the real function of the tool.
And I suspect that was not accidental.
Because “Power Query” is a brand name.
But “Get & Transform” is an explanation.
One energises marketing. The other restores meaning.
That, to me, looks like an attempt to correct drift. To reconnect the tool to its actual purpose. To stop people imagining that this was some general-purpose replacement for every older Excel technique, every database function, or every piece of system design thinking.
Yet the branding pressure never fully went away. The official docs still speak of Power Query, while Excel users still see Get & Transform in the ribbon. So even Microsoft seems to have ended up with a compromise: retain the powerful brand, but keep the descriptive surface.
The real problem: capability is not identity
This is where my Play-Doh analogy comes in.
You can shape Play-Doh into an elephant. That does not make it an elephant.
You can shape it into an aeroplane. That does not make it an aeroplane.
Likewise, you can use Power Query to imitate or approximate all sorts of things. But that does not change what category of tool it fundamentally is.
A tool’s capability is not the same thing as its identity.
Power Query can sometimes be stretched into tasks that sit outside the spirit of ETL. That does not mean those tasks are where it belongs. It does not mean they are the best use of it. And it certainly does not mean the tool has somehow become a replacement for relational architecture, process design, or lateral problem-solving.
That is the distinction that social media often collapses.
Why the mislabelling persists
The reason this keeps happening is simple.
Social media rewards the person who appears to have discovered a clever new way to do something.
It does not reward the person who says, “Actually, this problem was solved more elegantly years ago by using the right architecture.”
So if someone can use Power Query to recreate a clumsy, indirect, over-engineered version of something that could have been solved more simply another way, that can still perform very well online. It becomes content. It becomes brand-building. It becomes a route to audience growth.
And once enough people build books, courses, identities, and followings around that interpretation, the interpretation becomes self-reinforcing.
At that point, a tool is no longer just a tool. It has become a social-media symbol.
Why this matters beyond Power Query
This is why the recent Agent Mode → Edit with Copilot shift is so interesting.
If the reported change is real — and the current evidence strongly suggests it is — then it may be another example of Microsoft trying to drag a feature back toward a more grounded description after a more expansive label encouraged broader assumptions. George Mount’s summary is that Agent Mode in Excel for the web was announced on December 9, 2025, and the label vanished around March 6, 2026. Microsoft’s own January 2026 updates still used the Agent Mode wording, so the apparent change is recent.
That would fit the same pattern.
A grander name invites grander expectations.
A narrower name tries to restore realistic expectations.
And when users or influencers push a feature outside its intended lane, disappointment follows. They complain that it is incomplete, unfinished, flawed, or not ready. But sometimes the deeper problem is not that the product failed. It is that the product was being made to carry meanings it was never designed to carry.
That, in essence, is what happened with Power Query.
The deeper lesson
The Power Query story is not really about whether Power Query is good.
It is good.
It is useful.
It is important.
Microsoft’s own documentation is clear that it is a serious and capable data-connectivity and ETL technology used across multiple Microsoft products.
The issue is not quality.
The issue is misdescription.
When a tool is marketed one way, taught another way, understood a third way, and used a fourth way, confusion is inevitable.
And in that confusion, a whole generation of users can be nudged toward the wrong mental model.
That is the real cost.
Because once people start thinking an ETL tool is a substitute for architecture, or that importing large volumes of data means databases are no longer needed, or that every business pain is now a Power Query opportunity, they are no longer just learning a feature.
They are being trained into a distorted view of the digital landscape.
Final thought
So why was Power Query called Power Query, then surfaced as Get & Transform, and still effectively referred to by both names?
Because it sits at the intersection of two competing forces.
One force is marketing, which wants a bold, memorable, exciting label.
The other is meaning, which wants the user to understand what the tool is actually for.
Power Query is what happens when marketing wins the launch, and meaning comes back later to repair the damage.
And now, with Copilot, we may be watching the same drama all over again.
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