Excel has been a firm favourite for working professionals for many years, and for good reason. Its wide capabilities and ease of use have made it critical in all manners of business, education, finance, and research. However, as organizations move toward an AI-first strategy, a new question has emerged:
Is Excel still the best tool for the modern data analyst?
Enter Python. This programming language has gained significant traction, evolving from a tool to 'automate the boring stuff' into the undisputed leader in data science and infrastructure management.
The 2026 Update: What About "Python in Excel"?
The most significant shift since this guide was first published is Microsoft’s official integration of Python directly into the Excel grid. Using the =PY function, users can now leverage libraries like pandas and Matplotlib without leaving their spreadsheet.
Does this replace standalone Python? Not quite. While Python in Excel is a powerful bridge for ad-hoc tasks, standalone Python remains essential for:
-
Large Datasets: Handling millions of rows that would still "choke" a standard .xlsx file.
-
Production-Grade AI: Building autonomous AI Agents and robust data pipelines.
-
Security & Auditing: Ensuring data remains in a controlled, code-based environment.
| Feature | Microsoft Excel | Python (Standalone) |
| Data Volume | Max ~1M rows; fragile with large files. | Unlimited; built for "Big Data." |
| Automation | VBA & Macros (Harder to scale). | Scripts & AI Agents (Highly scalable). |
| Accuracy | Prone to manual formula & copy-paste errors. | Code-based; easy to audit and reproduce. |
| Advanced AI | Basic predictive add-ins. | The industry standard for Machine Learning. |
| Cost | Subscription-based (Microsoft 365). | Open-source and free to use. |
The Limitations of Excel
Consultants and IT experts have voiced concerns over how fragile spreadsheet software can be for high-stakes analysis. Key challenges include:
- Syntax Errors: Excel is notorious for errors when copying and pasting data in specific ranges.
- Security Risks: Storing sensitive information in spreadsheets can be risky without robust version control.
- Processing Speed: Complex equations and large datasets often lead to slow performance and "crashes."
The Python Advantage
Python has developed a massive global following as professionals realize its untapped potential. It is now the world’s most popular computing language, with a popularity share of nearly 30 percent, beating its closest competitors (C/C++) by double.
- Higher Incomes: According to 2025/26 UK market data, jobs requiring Python skills command an average salary of £72,000, compared to approximately £39,000 for roles limited to Excel.*
- Open-Source Innovation: With over 500,000 custom-built software packages (like TensorFlow for machine learning) on the PyPI repository, "Pythonistas" can leverage the latest global research for free.
- Versatility: This flexibility explains why the CIA has used it for security, Pixar for producing movies, and Spotify for recommending songs.
- Community Support: Backed by over 8 million developers, Python offers an unparalleled support system of tutorials, hackathons, and global conferences like PyCon and PyData.
Who Benefits from Learning Python?
Python is a diverse tool that adds value to almost any professional role:
- Data Analysts: Automate the entire pipeline from data extraction to final visualisation, saving hours of manual work.
- Finance & Accounting: Manipulate massive datasets to detect inconsistencies and build predictive financial models.
- Marketing & SEO: Automate data collection from search engines, social media sentiment analysis, and campaign performance checks.
- Journalism: Rapidly sort through vast amounts of information to find the "story" hidden in the numbers.
Excel vs. Python: The Verdict
The evidence suggests that both tools have their place. Excel is a brilliant entry-level tool and remains a quick-and-easy way to manage small datasets.
However, for the modern professional aiming to progress, Python is the key to standing out. It is faster, more powerful, and offers the scalability needed for the next decade of data work. After all, if you want to be a "star" data analyst, Python is no longer a luxury, it is a requirement.
Learn Python with Cambridge Spark
Ready to future-proof your career? We offer a L4 Data Analyst Apprenticeship where you can learn advanced Python, big data processing, and machine learning while remaining in full-time work.
*Market Data on 2025/2026 UK salaries - IT Jobs Watch / Morgan McKinley