不會寫程式也能做數據分析：用 AI 看懂你的資料
有一堆 Excel 卻不知道怎麼分析？用 AI 你只要用「問」的，它就能幫你算、找趨勢、做圖表。這篇教你怎麼開始。
The Data is There, But You Can't Understand What It's Saying
Many people have a lot of data on hand - sales records, survey results, website data - but get stuck on "what's next?" Not knowing how to write formulas or understand statistics, the data is just a pile of idle numbers. AI has lowered this barrier: you ask, and it helps you calculate, find trends, and create graphs.
Three Ways AI Helps You with Data Analysis
- Ask Your Data Directly: Upload your file, and ask in plain language, "Which month sells the best?" or "Which type of customer repurchases the most?"
- Generate Formulas: Don't know which function to use? Describe your needs, and it will give you Excel/Sheets formulas.
- Create Charts and Insights: Automatically draw suitable graphs and tell you the key points in plain language.
Mainstream Tools, Choose According to Your Needs
- Upload Files and Ask Directly, with Graphing Capabilities: ChatGPT (data analysis function), Rows, Sourcetable.
- Only Need Excel Formulas: GPTExcel, Ajelix, Formula Bot.
- Data is in a Database: Chat2DB - generate SQL queries by talking.
- Advanced Analysis/Collaboration: Hex, Deepnote, Quadratic.
A Practical Analysis Process
- Clarify What You Want to Know: Don't be aimless, define the problem first ("want to know which products to promote").
- Organize Clean Data: Consistent fields, remove duplicates, AI can also help you clean.
- Upload and Ask: Use plain language to ask step by step, and ask it to explain its findings.
- Ask it to Draw Graphs: Ask AI to suggest and generate the most suitable charts.
- Verify Yourself: AI may calculate incorrectly, so verify important conclusions yourself.
Things to Note
- AI May Calculate Incorrectly or Fabricate: Numerical conclusions must be verified.
- Be Mindful of Sensitive Data Privacy: Customer personal information, financial data, be cautious when uploading to the cloud, and consider using local solutions.
- Don't be Deceived by Pretty Charts: Good-looking charts don't necessarily mean correct conclusions, look carefully at the data source and logic.
TheAI Academy Summary and Review
Honestly, AI has made "data analysis" - which originally required programming and statistical knowledge - into "just asking questions". But this also has a pitfall - it's too good at giving you impressive-looking answers, so you need to be more skeptical and verify yourself.
Start with a dataset you have on hand, upload it, and ask a few questions. You'll be surprised at how simple analysis can be. Extended reading: Using AI to Handle Spreadsheets.
A brief review: AI makes data analysis "just asking questions", but it's too good at giving pretty answers, so you need to verify yourself.
Data Sources
Frequently Asked Questions
不會寫程式能做數據分析嗎？
可以。用 AI 上傳檔案後用白話提問，它就能幫你計算、找趨勢、生成圖表並解釋發現。
數據分析該用哪些 AI 工具？
上傳直接問用 ChatGPT、Rows、Sourcetable；只要公式用 GPTExcel、Ajelix；資料庫用 Chat2DB；進階用 Hex、Deepnote。
用 AI 分析資料要注意什麼？
AI 會算錯也會編，重要結論務必自己驗證；敏感資料留意隱私；別被漂亮圖表誤導。
怎麼開始用 AI 分析資料？
先定清楚想知道什麼、整理乾淨資料、上傳用白話提問、請它畫圖，最後自己驗證關鍵結論。