Stop guessing in meetings: clean the data yourself, build a dashboard people trust, and let AI write every formula and chart you need.
You are asked how the business is doing, and the honest answer is that nobody quite knows. The numbers live in four different tools, last quarter's spreadsheet does not match this one, and the report someone built two years ago has been quietly broken for months. This no-code course makes you the person who can actually answer: pull real data out of the systems it hides in, clean it, check it before you trust it, and ask it questions that hold up. You will learn the metrics that run a business - revenue, retention, customer acquisition cost, lifetime value, funnels - and what each one hides when you read it wrong. Then you will build dashboards in free business intelligence (BI) tools like Looker Studio, compress a finding into one slide a decision-maker can act on, forecast with the uncertainty stated out loud, and schedule the whole thing so the numbers arrive without you touching them. AI writes every formula, query, and chart spec you ask for, which is why this needs no programming and no SQL, the query language analysts normally learn first.
Built by Lakshya Kumar
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Sign in to applyFinished the tasks? Take the prompt to your AI and get tested on it. We copy the prompt and open the app — just paste it in.
Export it cleanly, fix the mess with AI, and build the reflex that catches a wrong number before it reaches someone important.
Pivot tables, the handful of formulas that carry most analysis, and the trick of letting AI write any formula from a plain-language ask.
Revenue, growth, retention, CAC and LTV, unit economics, and funnels - what each one actually answers and when it lies.
Ask it as a testable hypothesis, cut it by segment and cohort, and you stop mistaking a vanity metric for a real result.
Free BI tools like Looker Studio, choosing the right chart for each question, clean layout, and auto-refresh so it stays alive.
Compress an analysis into a one-slide narrative execs act on, with AI drafting the commentary and you owning the recommendation.
Simple trend projection, scenario models in a sheet, and stating uncertainty out loud instead of pretending a forecast is a fact.
Scheduled reports, threshold alerts, and connecting sheets to live sources so numbers arrive without you touching them.
A weekly reporting rhythm, self-serve dashboards a team runs without you, and the habits that make you the person who knows the numbers.
Complete all modules, then submit the required number of capstone projects. Each must earn a passing rating from an admin reviewer.
Build a dashboard for a real business or a public dataset that refreshes on its own from a connected source. It must answer five named questions a decision-maker actually asks (write the five out), show at least four metrics with the right chart for each, and include a short data-source note stating where each number comes from and how fresh it is. Submit the live link plus a one-paragraph tour of what each section answers.
Paste this into any AI chat. Fill in the bracketed parts with your context — you'll get back a straight answer on whether this belongs on your plate.
I'm learning business analytics on Capstok - a no-code course covering pulling and cleaning data, spreadsheets and pivot tables, business metrics, dashboards, storytelling, forecasting, and light automation. Act as my analyst: write the formulas, queries, and chart specs I ask for, explain what each number means, challenge my conclusions, and flag when the data can't actually support the claim I want to make.
Pick one real question, answer it with data, and write it up so someone could act on it: the question and why it mattered, the data and how you checked it was right, the finding with the chart that proves it, and a specific recommendation. Show at least one moment where the data contradicted your initial assumption. Two to four pages or one tight deck.
Package a repeatable weekly report that someone with no analytics skill can produce in under 15 minutes. Include the source sheet or template, a step-by-step runbook, the standing questions it answers, and one filled-in example week. It must survive being handed to a colleague - test it by writing instructions precise enough that a stranger produces the same output.