How to Understand What Your Data is Telling You with Copilot
Spreadsheets full of numbers don’t speak for themselves. Copilot can read your data and tell you the ‘so what’ — what changed, what matters, what to do.
What it is
Data analysis used to require either skill (in Excel, in pivot tables, in interpretation) or asking someone with the skill. Copilot collapses that gap dramatically. Show it a spreadsheet and ask ‘what’s this telling me?’ and within seconds you have a plain-language explanation of trends, outliers, and what they probably mean.
The catch is that Copilot is interpreting what it sees, not necessarily what’s true. It can spot trends correctly. It can also project trends incorrectly, miss context, or apply the wrong frame. For data that’s important — financial, operational, decisions — use Copilot’s interpretation as a starting point, then verify the underlying numbers and the logic of the conclusion.
The most useful pattern is to ask Copilot for the ‘so what’ and the ‘what should I do’. Numbers without action are just noise. ‘Revenue grew 12%’ is data; ‘revenue grew 12%, driven by enterprise sales, suggesting we should double down on enterprise marketing’ is insight. Copilot can produce both, but you need to ask for the second one explicitly.
When to use this
- When you have a spreadsheet of numbers and need the headline.
- When you’re preparing a report and need a ‘what does this mean’ paragraph.
- When you need to explain data to a non-technical audience.
- When you want to identify trends, outliers, or notable changes quickly.
How to do it
- Open the spreadsheet (or summarise its structure if you can’t share it directly).
- Tell Copilot what the metric is and what success looks like.
- Ask for trends, highs/lows, and notable changes.
- Ask for the top 3 insights — focus, not exhaustiveness.
- Ask for ‘what should I do based on this’ or ‘what questions does this raise’.
- Verify the underlying numbers and logic before presenting.
- Use the output to write a short summary for your audience.
Best practices
- Tell Copilot what the metric represents. Numbers without context produce wrong interpretations.
- Ask for top 3 insights, not ‘all insights’. Focused output is more useful than exhaustive output.
- Verify before presenting. Especially percentages, totals, and comparisons.
- Use simple visuals for one insight at a time. Don’t dump 12 charts on a slide.
Common mistakes
- Trusting Copilot’s interpretation without checking the numbers. AI hallucinations in numerical context can be subtle.
- Asking ‘analyse this data’ with no context. Generic output, often wrong frame.
- Confusing correlation with causation. Copilot sometimes confidently claims causal relationships that the data only shows correlation for.
The Copilot Readiness Guide gives you the 25-question scorecard, the 4-category risk audit, and the 30-day plan to fix permissions, content quality, and sensitive content before go-live.
Get the Copilot Readiness Guide — $39 →FAQ
How do I use Copilot in Excel to analyse data?
Open the spreadsheet, click Copilot in the ribbon. Ask in plain English: ‘What’s the trend in revenue over the last 6 months?’, ‘Which customers are growing fastest?’, ‘Show me anomalies in this data.’ Excel Agent (rolled out 2026) can build pivot tables, charts, and formulas autonomously based on your prompt.
What is the Excel Agent in Microsoft 365 Copilot?
Excel Agent is a 2026 Copilot capability that performs multi-step data analysis automatically — building tables, applying formulas, creating charts — based on natural-language instructions. Unlike basic Copilot which suggests, the Agent acts directly on your spreadsheet. Available with or without a paid Copilot licence; admin enablement required.
Can Copilot do statistical analysis in Excel?
Yes for basic stats (mean, median, standard deviation, correlation). For advanced statistics (regression, hypothesis tests, time series), Copilot can suggest formulas but verify the methodology. Copilot can hallucinate confident-sounding statistical claims that don’t pass scrutiny — always sanity-check.
Why does Copilot give different answers about the same data?
Three reasons: small phrasing changes in your prompt produce different interpretations; Copilot samples data when the dataset is large, so different samples give different results; and underlying model behaviour has some randomness. For decisions that matter, ask Copilot to show its work — formulas, calculations, source rows — so you can verify.