Strategy course

Use data with more confidence, without becoming an analyst.

Read a metric by checking what was counted, who or what it was divided by, and whether the comparison uses compatible periods. A bigger count can coexist with a lower rate. Work through the example before deciding what a chart means.

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Try a practical exercise

A starting goal

I need to use numbers at work without becoming an analyst. Teach me to ask the right question of a chart, read rates and averages properly, and spot when data is being used badly.

Change any word so it fits your situation. The course is built from what you type and a few setup questions.

A professional reviews a chart and distribution before approving a workplace decision. — Data literacy **Data literacy for non-analysts**
7 to 30 lessons.

Best for: Strategy & decisions
Prerequisites: No formal prerequisites
Course length: 7 to 30 lessons
Pace: Yours. One lesson at a time, as often as you like.
Access: Available on the App Store and Google Play, with an optional early testing list

An original website exercise

Compare a count and a rate without mixing them.

Imagine two complete weeks of a website test, using the same definitions: week A has 20 sign-ups from 100 eligible visits; week B has 30 from 200. These are made-up figures.

01

Calculate each rate

Week A is 20 divided by 100, or 20%. Week B is 30 divided by 200, or 15%. Keep each numerator with its own denominator.
02

Describe both changes

Sign-ups increased by 10, while the visit-to-sign-up rate fell by 5 percentage points. Neither statement cancels the other.
03

Check what the data cannot tell you

The example does not explain why the rate changed. Different visitor intent, measurement or other conditions could matter. Do not attribute the result to a page edit from these totals alone.

Worked example, not a learner result

We received more sign-ups in week B, but a smaller share of eligible visits became sign-ups: 30 at 15%, compared with 20 at 20%. We need comparable traffic and measurement details before explaining the difference.

Now explain the result without saying "conversion improved" just because the count rose. If your denominator is people in one week and events in the other, stop and fix the comparison first.

Start free in Cadence and describe what you want to learn. Answer the setup questions to create your own course.

Right for now

If any of this sounds familiar, start here.

Every lesson connects to a conversation, decision, or habit you can change between lessons.

Dashboards leave you unsure

Connect each metric to the decision it is meant to inform.

Percentages sound convincing

Check the denominator, comparison group, and time window before trusting the claim.

Charts drive the meeting

Spot visual choices that exaggerate, hide, or confuse the real comparison.

You work with analysts

Ask for the evidence and limits you need without prescribing a technical method.

Example course outline

One way this course could begin.

The lessons follow a clear sequence, so the next practical move is waiting when you come back.

Decision-first questions

Start with the choice, then decide which evidence matters.

Metric judgment

Read rates, averages, segments, distributions, and forecasts in context.

Evidence checks

Notice data quality problems, selection bias, uncertainty, and weak causal claims.

Clear recommendations

State what the evidence supports, what remains unknown, and what to do next.

Example course outline 7 to 30 lessons

Data Literacy for Non-Analysts

Lesson 1 Start With the Decision

Turn a workplace choice into one decision question with a clear action at stake

Lesson 2
What Exactly Is Measured

Define a metric by naming its numerator, denominator, population, and time window
Lesson 3
Denominators Change the Story

Choose a denominator that matches the decision and explain how a different one changes interpretation

Course arc

From vague intention to repeatable moves.

Cadence turns the course into a returnable habit: short lesson, quick check, review, and the next useful step.

01 / 04

Frame the decision

Turn a broad request for numbers into an answerable workplace question.

Read the measures

Interpret denominators, averages, variation, and segments.

Test the evidence

Check quality, bias, causation, experiments, and uncertainty.

Write the brief

Combine the question, metric, evidence limits, and next step.

Example syllabus

Your course is built around your goal.

This outline shows one possible path. Your lessons and course length are created from your request and setup answers.

Module 01

Questions, Metrics, and Denominators

Frame decisions as answerable questions and define metrics with their populations and time windows

Lesson 1 Start With the Decision
Lesson 2 What Exactly Is Measured
Lesson 3 Denominators Change the Story
Lesson 4 Metric Choice Under Pressure
Lesson 5 Metric Definition Checkpoint

Module 02

Rates, Averages, and Segments

Interpret rates, averages, distributions, and segments without confusing unlike groups

Lesson 6 Rates Show Relative Change
Lesson 7 Averages Hide Variation
Lesson 8 Read the Distribution
Lesson 9 Segments Reveal Differences
Lesson 10 Numbers in Combination

Module 03

Evidence Quality and Uncertainty

Diagnose data quality, selection bias, sampling limits, and uncertainty in workplace evidence

Lesson 11 Is the Data Fit for Use
Lesson 12 Who Got Counted
Lesson 13 Samples Need Boundaries
Lesson 14 Uncertainty Is Information
Lesson 15 Evidence Quality Checkpoint

Module 04

Causation, Experiments, and Forecasts

Separate correlation from causation and judge experiments and forecasts for decisions

Lesson 16 Correlation Is Not Cause
Lesson 17 Experiments Change One Thing
Lesson 18 Experiment Results Need Context
Lesson 19 Forecasts Are Conditional
Lesson 20 Causal Decision Checkpoint

Module 05

Charts, Dashboards, and Analyst Collaboration

Read visual evidence and ask analysts focused questions that improve decision quality

Lesson 21 Charts Make Comparisons Visible
Lesson 22 Chart Integrity Matters
Lesson 23 Dashboards Need Decisions
Lesson 24 Ask Analysts Better Questions
Lesson 25 Evidence Communication Checkpoint

Module 06

Decision-Ready Data Briefs

Produce and rehearse five-part decision briefs from self-contained workplace evidence

Lesson 26 The Five-Part Brief
Lesson 27 Make the Metric Auditable
Lesson 28 State Evidence and Uncertainty
Lesson 29 Recommend a Proportionate Next Step
Lesson 30 Decision-Ready Data Brief

How learning works

Read, listen, check your understanding, then keep going.

Learn at your own pace

Each lesson builds on the one before. Keep going when you want to.

Reading and audio

Read the lesson or play its audio when listening fits your day better.

Checks when useful

Lessons can use quizzes, written responses, or guided practice. A lesson can also teach without adding a forced exercise.

Progress and support

Track completed lessons, keep a streak, set reminders, and ask the in-lesson coach for help.

Know the limits. Cadence supports guided self-learning. It does not award an accredited degree or professional certificate, and important claims in a lesson should be checked against reliable sources.

Free to read first

Guides on the same skill.

Course questions

What to know before you start.

Who is Data Literacy for Non-Analysts for?

People who use dashboards, reports, or workplace metrics and want to question the evidence, explain uncertainty, and make better decisions without becoming analysts.

Do I need any prior experience?

No formal prerequisites are required. The course is designed for guided self-learning, and it is most useful when you bring a real situation or goal to the lessons.

How long does the course take?

Most courses run 7 to 30 lessons. Cadence sizes yours after the setup questions, and you choose your pace.

What is the learning format?

Lessons can be read or played as audio. The course includes quizzes or practical checks where the lesson calls for them, plus progress tracking and Ask Coach inside lessons.

Does this course award a certificate or degree?

No. Cadence is for practical self-learning and does not award accredited degrees or professional certification.

Start today

Example first lesson: Start With the Decision

Get Cadence, type what you want to learn, and answer the setup questions to create your course.