Your first data story

Where to go next

Look back at what you can now do, plan your capstone question, and see how this course leads into statistics, spreadsheets, SQL and beyond.

By the end of this lesson you can see how this course leads into statistics, spreadsheets, SQL and beyond.

Why it matters

Learning sticks when you know where you have been and where you are going. Five minutes looking back, and a clear next step, turn a finished course into the start of a skill.

The idea in plain words

Think of learning to ride a bicycle. First you learn to balance. Then to steer. Then to ride on real roads, with traffic. Each step uses the last one.

This course was the balancing step. You can now read a table, ask it a clear question, get an answer with a formula, draw an honest chart and write a data story. The next courses build on exactly these skills.

S1, Principles of Statistics, comes next: it takes averages, spread and "together is not because" much further.

Statistics: the study of collecting, summarising and drawing careful conclusions from data, including how sure you can be.

SQL: a language for asking questions of large databases. Its ideas (pick rows, pick columns, count, add up) are the ones you used in Module 3.

See it done

Task: look back, then get ready for your capstone.

Look back. Here is what you can do now, grouped into three kinds of skill.

Every skill in these boxes, you have practised on real or labelled data.

Pick one skill you feel least sure about. Go back to that lesson and do its "Your turn, alone" again. It takes about ten minutes.
Know your capstone question's shape. The capstone gives you your own question: how one measure (population, or CO₂ per person) changed in 4 countries from a start year to 2024. Each learner's countries, measure and start year are different.
Practise the first step now. Open the country tab and filter country to Kenya. Read Kenya's population in 1990 and in 2024. Write them in millions, rounded to one decimal place. You should get 22.9 million in 1990 (22,892,655 people) and 56.4 million in 2024 (56,432,946 people). This is exactly how the capstone starts.

Amara and Lucía's plans: Amara wants to note her cost prices next week, so she can finally answer the profit question. Lucía wants to run her survey again later in the year, to see whether travel times change.

Your turn, with help

Turn this wonder into a clear question the country data can answer: "Is Kenya growing?"

Hint: "growing" in what? The data has population and CO₂. Pick one, and add when.

Show a model answer

"How did Kenya's population change from 1990 to 2024?" (Rows: country is Kenya. Columns: year and population.)

Your turn, alone

Practise the capstone shape: pick any 4 of the 17 countries and one measure, and write the question ("How did ... change in ... from ... to 2024?"), plus the rows and columns it needs.
Name the chart type that question needs, and why (lesson 4.5).
Name one trap from Module 5 your answer could fall into, and how you will avoid it.
Which course would you like to take next, and why?

Check your plan

There is no single right answer. A strong plan:

Has a question with a what (one measure), a where (4 countries) and a when (a start year and 2024), and names the rows (those countries and years) and columns (country, year, and the column or columns the measure needs: population for population; both co2_million_tonnes and population for CO₂ per person).
Picks a line chart for change over time, or a bar chart for comparing countries.
Names a real risk, for example "comparing totals for big and small countries: I will use per-person figures".
Gives a reason linked to your goals.

Watch out

Choosing a question the data cannot answer. Check the columns first.
Too big a question. "Everything about Africa" is not one question. Pick one measure, a few countries, and a time period.
Stopping practice. Skills fade if you do not use them. Try one small question a week on any data you meet.

Say it back

Which course comes next in the DataMedics path?
What two measures does the country data hold?
Name one skill from each of Modules 1, 3 and 5.

Show the answers

S1, Principles of Statistics for Data Analysis.
Population and CO₂ (carbon dioxide).
For example: Module 1, reading a cell address; Module 3, COUNTIF; Module 5, spotting a cut-off axis.

What is next

You have finished the lessons. Next come this module's assignment (a full practice run of the capstone) and its test. Then the final exam, which checks you can use these skills on questions you have not seen, and the capstone, your first data story on real data, in your own slice of the world.

Data in this lesson: Global Carbon Budget (2025); UN World Population Prospects (2024), processed by Our World in Data. Licensed under CC BY 4.0 (UN data: CC BY 3.0 IGO). Extract and continent labels by DataMedics.