Monday

The front door of Starling Commons stands open, as it always does. Inside, members tinker at workbenches and read in the quiet corner.

Comet zooms in waving a letter. "The Commons council needs us!" she says. "They want to know what the Commons should add next."

"I vote for a launch pad," she adds with a grin. "Let's start building today!"

Wren reads the letter twice. "What do you notice?" he asks. "The council asked what members want, not what we want."

Nova glides down from a high shelf, her lights glowing softly. "Would you like a hint?" she asks. "Find out what the members would really use."

Comet turns to you. "You are our data analyst. Where do we start?"

Starling Commons is the community maker hall in the crew's hometown. It has workbenches, a reading corner and a screen at the front desk.

It has 120 members. Over twelve weeks, the crew will plan, run and study a survey of those members called Commons Count.

The Commons, its members and every number about them are made up for the story. The data skills you practice are real.

This course is unplugged. You need paper and a pencil, never an app, a website or an account.

In this course, data are the raw counts, answers and measurements people collect.

Information is the facts and patterns pulled from data.

Data give people chances to spot trends, make connections and address problems.

A list of sign-in times is data. "Most of these sign-ins were in the evening" is information pulled from that list.

"What should the Commons add next?" is a good start, but data cannot answer it directly yet.

A sharper question names what to measure. Who would use an addition, and how often would they use it?

Here is one sharper version: "Which addition would the most members use at least once a week?"

Now the crew knows what to count: members, additions and how often.

Strong start, data analyst. Tomorrow the crew works out what it can actually measure.