Your First Data Analysis with AI

Take a real dataset or spreadsheet and upload it to ChatGPT or Claude. Let AI find patterns, trends, and correlations — without needing any explanation from you.

Why We Start with Real Data

You might think data analysis is a job for statisticians — people with advanced Excel courses and mathematical formulas. That's no longer true. Modern AI can "read" spreadsheets the way you read a letter. It sees patterns that would be invisible to you and explains them in plain language.

It's like having an assistant who reads your spreadsheet and tells you what's in it. You don't need specialized training. You just need a dataset and curious questions.

Your Task

Find yourself a dataset. This could be:

• Your own data: A household budget (what do you spend on?), your last 50 Amazon purchases, your training times from your fitness app, visitor numbers to your blog.
• Real public data: European climate data, movie ratings, election statistics, football player data — just google it.
• A sample dataset: If you don't have data, create one: 10-15 rows with products and sales numbers, or students with their grades, or countries with their CO2 emissions.

Upload the data as CSV, Excel, or simply as a table to your AI chat. Both Claude and ChatGPT can process files. Then write a message like this:

Here are my [household budget / sales data / training times] from the last [time period]. What stands out? Where do I spend the most? Are there patterns I haven't seen? Give me a visual summary.

What to Observe

Pay attention to three things while AI analyzes your data:

1. The speed: How quickly does AI find patterns that would take you hours? Does it talk about correlations, seasonal fluctuations, or outliers — without you asking? That's the real power: AI does in seconds what takes days by hand.

2. The visualizations: AI doesn't just describe — it suggests graphics. Bar charts, trend lines, comparisons. Remember which visualization shows your data best. This helps you later create better graphics yourself.

3. The questions you forgot to ask: Maybe AI says: "Interestingly, your spending in March is 15% higher than average — this could be due to [reason]." That's an insight you might not have seen. Note these observations — they show you how to think differently about data in the future.

A Thought to Take Away

Some people think AI analyses sound "too good to be true." That's not wrong — but it's also not the opposite of valuable. AI finds real patterns in your data. Your job isn't to distrust it, but to question its results: Does that make sense to me? Can I understand it? Is the conclusion fair?

That's professional partnership, not blind trust.