Getting real work done · for data analysts
Finishing real analysis work with AI
A draft query is the start of the work, not the end. Analysis counts when a stakeholder reads it and makes a decision. That needs a clear question, correct numbers, a chart that shows the point, and a summary that states what the data does and does not support.
Getting real work done means using AI to reach that finished result faster without lowering its quality. It also means knowing which parts of the job need your own judgment, such as choosing what matters and deciding how confident to be.
Where it comes up
Explaining a metric change to a stakeholder
Revenue fell compared with last month and a director wants to know why. AI can help draft the breakdowns and the write-up. You decide which explanation the evidence supports and how firmly to say it.
Narration for a dashboard
Write the two or three sentences that tell a reader what each chart shows and what to watch. AI drafts from the figures. You remove any sentence that overstates the data.
An analysis brief for a decision
A product team needs a recommendation on whether to extend a pricing test. AI can structure the document and test your reasoning. The recommendation and its stated limits are yours.
What it looks like at each band
E1 · Foundational
Produces draft queries and summaries with AI, then finishes the analysis mostly by hand. Quality depends more on manual effort than on how AI was used. Sometimes sends narrative that restates the chart without saying what it means.
E2 · Proficient
Uses AI through to a finished analysis that answers the question, with correct figures and a readable summary. Meets the request on routine work. Knows which parts, such as the conclusion, to write personally.
E3 · Distinguished
Delivers complete analysis on open-ended questions where the right approach is not obvious. Uses AI to explore options and draft, and personal judgment to decide what matters. States uncertainty in plain terms a non-analyst can follow.
E4 · Exceptional
Consistently delivers analysis that changes decisions and raises the team’s standard, under deadline. Is deliberate about where AI helps and where it does not. Can show others how a finished piece was built and checked.
Common mistakes
Sending the query result as the answer
A table of numbers is not an analysis. The stakeholder needs to know what changed, why it matters, and how sure you are.
Narration that repeats the chart
"Revenue went up in March" tells the reader what they can already see. Say what drove the change, or say that the driver is not yet known.
Hiding the uncertainty
AI drafts tend to sound certain. If the sample is small or the data is incomplete, say so near the top, not in a footnote.
A worked example
A director asks why trial-to-paid conversion fell last month, with an answer needed by the afternoon.
Ask AI why conversion might have dropped, then send the director its list of five common reasons.
The list comes from general knowledge, not from your data. The director receives speculation presented as analysis and may act on a cause that did not occur.
Ask AI to help list candidate explanations, then write queries that break conversion down by channel, plan, and signup week. The drop sits in one paid channel that changed its targeting mid-month. Draft a short note with AI from those results. Edit it to lead with the finding, show one chart, and state that the channel change is the likely cause but other factors were not tested.
AI speeds up the drafting and the brainstorming. The finding comes from the data, the analyst decides how firmly to state it, and the director gets an answer to act on.
The full study guide for this skill, for every role, is Getting real work done. The other five skills for data analysts are on the AI skills for data analysts page. A one-page summary is in the AI-assisted work checklist.
See where you stand
The free check grades getting real work done and the other five skills in about fifteen minutes. Nobody sees the grade but you.
Then build the skills and prove it. The three steps for data analysts list the courses and templates that fit the work.