As an Excel trainer and course creator who often covers more advanced topics, I get a lot of questions about these newer features, particularly Python in Excel and Copilot in Excel. “When should I use these?” “How do I actually use them well?” “Does this mean regular Excel isn’t good enough anymore?”

I get it. And adding another layer to this maze with Copilot and Python all working together inside Excel is wild, and for a lot of people a little anxiety-inducing.

So in this post, I want to talk about when Advanced Analysis with Copilot for Python in Excel is actually the right fit for your workflow, and when it might not be.

Because let’s be clear: not every shiny new AI-powered Excel feature is meant to replace your beloved PivotTables, SUMIFs, or even basic formulas. This isn’t magic. It’s a tool. And like any tool, it has moments where it really shines… and other times where it just doesn’t make much sense.

First off, what exactly is Advanced Analysis with Copilot?

Advanced Analysis is Microsoft’s latest feature that combines Python scripting directly in Excel using Copilot’s AI assistance. The idea is straightforward: you get to run Python code seamlessly within your Excel workbook, guided by Copilot. It’s designed for sophisticated analytical tasks, including time series forecasting, quick machine learning modeling, and data visualizations.

Here’s what’s cool about it:

• It generates Python code snippets you can run directly in Excel.
• It covers use cases that Excel traditionally struggles with like time series, machine learning, clustering analysis, advanced visuals, and quick hypothesis testing.
• It’s auditable. You get to see the Python code it generates. You can review, tweak, or adapt the generated Python code as needed.
• It uses data that’s already in your workbook. No need to juggle CSVs or open up a separate Jupyter Notebook to do your Python-backed insights.

Here’s what’s less cool:

• It’s not really designed to be super collaborative or shareable. The analysis is quick, iterative, exploratory… more like your own private analytical playground. Sure, you get the Python code generated by Copilot, but actually working it into more permanent reports or analyses is probably going to take some muscle. Plus, there’s the unavoidable fact that a lot of people on your team may not even know Python.
• And, drumroll please: this tool isn’t foolproof, isn’t meant for beginners, and definitely shouldn’t be taken as “right” 100% of the time. Like any AI tool, Copilot can, and will, occasionally deliver results that are a bit off-target.

Now let’s dive deeper into the specific scenarios when this really becomes the right tool to use.

When to embrace Advanced Analysis

You need rapid insights, not production-ready dashboards

Advanced Analysis is perfect for quick exploratory questions or what I’d call “back-of-the-envelope” data thinking. This isn’t your polished monthly reporting dashboard you’re sending off to stakeholders. It’s the quick glance into the crystal ball to validate a hunch or a hypothesis.

Maybe you need to rapidly check a correlation between customer churn and pricing, or forecast sales for the next month without setting up an elaborate forecasting model. Advanced Analysis lets you dive into the numbers quickly, guided by Python, to confirm or disconfirm your intuition.

If you get a good result, fantastic! If not, you just move on without spending hours wrestling with complicated models.

You’re exploring advanced scenarios beyond Excel’s traditional capabilities

Some analytical tasks, like clustering customer groups, running a quick regression model, or forecasting seasonal sales, are difficult or impossible in native Excel. PivotTables and slicers are fantastic for simple grouping and summarizing… but not so great for nuanced machine learning problems.

Copilot’s Advanced Analysis bridges the gap. It offers tools like ARIMA models for forecasting, linear regression models for quick predictions, and even K-means clustering right inside Excel.

If these are the types of tasks you frequently encounter, or want to explore, Advanced Analysis could quickly become a new power tool in your toolkit.

You understand a bit about Python (or at least want to learn)

To really get value out of Advanced Analysis, you need some basic familiarity with Python, or at least a willingness to learn as you go. Copilot will generate code snippets for you, but you have to be comfortable enough to understand generally what’s happening.

You don’t need to be a Python wizard. But if terms like “pandas,” “NumPy,” or “Matplotlib” don’t sound at least vaguely familiar, you’re going to find it harder to truly benefit. The beauty is that using Copilot helps you quickly gain exposure to Python. Think of it as having a mentor who gently guides you through the language, step-by-step.

You’re comfortable with ambiguity and quick iterations

Here’s where the analyst mindset becomes crucial. Analysis, by definition, deals with uncertainty. Copilot helps you rapidly test hypotheses and make informed guesses. But yes, sometimes it’ll be wrong, or at least imperfect.

The thing is, human analysts get things wrong too. Copilot doesn’t absolve you from having analytical intuition. Like a driver using Google Maps, you still need enough common sense to avoid driving into lakes or going entirely in the wrong direction.

Ambiguity comes with the territory, and if you’re comfortable with that, Advanced Analysis will feel intuitive and powerful.

When NOT to rely on Advanced Analysis

Okay, so we’ve covered where Copilot shines. But let’s quickly address where it doesn’t.

You primarily need routine reporting or basic calculations

If your job is mainly generating routine reports, basic aggregations, or simple visualizations, the complexity of Python and AI might be unnecessary. A PivotTable or even basic formulas and functions can often get the job done more quickly.

Sure, Copilot could probably help you here too, but you’re likely adding complexity without sufficient benefit.

You’re sharing your workbook widely, immediately

Advanced Analysis generates Python code snippets in your workbook. While you can audit and tweak this code, it’s not exactly packaged neatly for wide distribution. If your colleagues aren’t comfortable with Python, sharing this could be more trouble than it’s worth.

Use Advanced Analysis for your personal exploration, then perhaps transfer insights to native Excel features if broader sharing is required.

You’re uncomfortable with uncertainty in your workflow

Let’s be honest: Copilot is AI. AI, even incredibly powerful AI, sometimes produces off results. If you’re someone who needs to confirm every detail with external sources or deeply authoritative references at every step, Advanced Analysis might feel uncomfortable.

There’s nothing wrong with verifying rigorously, but the biggest advantage of Advanced Analysis (its speed and agility) can be lost if you constantly feel compelled to double-check everything manually. It’s about comfort level: can you trust your intuition and the general plausibility of results, or must everything be confirmed by a secondary source?

Should you dismiss Advanced Analysis if you don’t “need” Python tasks?

Interestingly enough, even if you don’t often tackle traditional Python tasks, Advanced Analysis might still offer real value for your workflow.

Here’s why: Copilot is trained on an enormous amount of data… way beyond just Excel’s built-in functions and formulas. A substantial part of this training corpus is Python code, which is precisely why Copilot excels at translating your analytical needs into Python operations. Python itself is a fantastic interpreter language for advanced analytical tasks: large language models (LLMs) alone struggle with direct mathematical computations, but they’re extremely good at generating Python code that can handle those operations effortlessly.

This means that sometimes Copilot’s recommendations might genuinely outperform Excel’s built-in Analyze Data tool or other basic AI features, even for seemingly straightforward tasks. It can surface correlations, insights, or patterns that your usual toolkit might overlook, simply because it draws on a much broader training base.

Beyond that, Advanced Analysis serves as a powerful educational resource. You’ll get rapid, practical exposure to Python concepts and analytical methods that you might otherwise never encounter. It’s a great way to expand your analytical skillset without the friction of diving deep into Python from scratch.

Final thoughts: Embrace the ambiguity, enjoy the speed

In the end, the key factor determining whether Advanced Analysis with Copilot for Python in Excel is right for you is comfort with ambiguity and your analytical intuition. Do you enjoy quickly iterating on ideas, using a tool that offers rapid insights at the expense of occasional uncertainty?

Analysis, after all, is often less about certainties and more about informed probabilities. Just like Google Maps or any other algorithm-driven tool isn’t always perfect, Copilot isn’t infallible. The analyst’s role is interpreting, evaluating, and yes, occasionally correcting the AI’s output.

Advanced Analysis isn’t a silver bullet, but it is an incredibly sharp arrow in your analytical quiver. If you’re ready to quickly test ideas, explore new analytical frontiers, and embrace a bit of ambiguity, this might just become your new favorite tool.

And if you still have questions, or want help integrating Advanced Analysis into your workflow, don’t hesitate to reach out. I’m always here to help you make sense of Excel’s evolving AI landscape and turn these innovations into real-world results.

The post How to understand Advanced Analysis with Python for Copilot in Excel first appeared on Stringfest Analytics.