In a world where data analysts are expected to know SQL, Python, BI tools, and even AI workflows – Excel is still standing strong. Some see it as basic or outdated, but that couldn’t be further from the truth. The reality is that Excel remains one of the most powerful and practical tools in a data analyst’s toolbox – even for advanced professionals.
Let’s dive into 5 key reasons why Excel continues to matter, and why it deserves a respected spot in your daily workflow.
✅ 1. Excel is the fastest sandbox for data exploration
Before you open Jupyter Notebook, connect to BigQuery, or build a Power BI dashboard – Excel is already open. It’s the fastest way to preview and explore your data.
Why it still works:
- Instantly scan, sort, filter, and summarize raw data.
- Perfect for quick validation and sanity-checks before deeper analysis.
- Sometimes, 2 clicks in Excel can replace 10 lines of code.
📌 For many analysts, Excel is like a sketchpad – a space to test ideas fast.
✅ 2. Excel is the universal language of business
One of Excel’s biggest strengths is that everyone in the business world knows how to use it – not just analysts. Finance, marketing, operations, HR – for them, Excel is often the default data tool.
Why this matters:
- You don’t need to train your audience – just send the file and they get it.
- It simplifies collaboration between teams, especially non-technical ones.
- No matter where your analysis starts – it often ends in Excel anyway.
📌 Excel is not the only tool you should use – but knowing when to use it is a superpower.
✅ 3. Excel is way more powerful than most people think
If you think Excel is just for simple calculations, you’re missing out. In skilled hands, it’s an advanced, flexible analytics engine.
What Excel can really do:
- Power Query: Clean, transform, and combine data like a pro – no code required.
- Data Models & Power Pivot: Build relationships, DAX metrics, and KPIs across tables.
- Pivot tables, advanced formulas, Solver, BI plugins – there’s so much depth.
- Database & API connections: Excel integrates with modern data ecosystems.
📌 It’s not a toy – it’s a fully capable tool for advanced data work.
✅ 4. Excel teaches structured and logical data thinking
Excel forces you to think in terms of rows, columns, dependencies, and rules. This mindset is foundational and directly translates into SQL, Python (Pandas), and working with data models.
Why it’s essential for growth:
- Excel helps you learn core concepts of structured data intuitively.
- Concepts like joins, filters, group by, and aggregation become second nature.
- It’s also a fantastic tool for learning and debugging messy data.
📌 Even if you move on to more complex tools – Excel builds the mental model you’ll use everywhere.
✅ 5. Excel is often the last step in real-world data workflows
You might process data in SQL, run models in Python, and build dashboards in Looker – but in many organizations, the final version still ends up in Excel. And that’s perfectly valid.
Why this is important to embrace:
- Excel is often where decisions are made, commented, and signed off.
- Knowing how to prepare your output for easy use in Excel adds real value.
- Finance, controlling, senior leadership – they all live in Excel.
📌 Excel isn’t your enemy – it’s the final mile of data in most companies.
💡 Summary – Excel isn’t outdated, it’s essential
Yes, Excel has limitations. But that doesn’t mean it’s irrelevant – quite the opposite. If you want to be an effective, flexible, and well-rounded data analyst, then knowing how to use Excel properly is a huge advantage.
It’s not a relic of the past. It’s a universal, adaptable tool that fits naturally into every stage of the data analysis workflow. Mastering it isn’t a step back – it’s what smart analysts do to move forward.
Prefer to read in Polish? No problem!
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The article was written by Kajo Rudziński – analytical data architect, recognized expert in data analysis, creator of KajoData and polish community for analysts KajoDataSpace.
That’s all on this topic. Analyze in peace!
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