DT9: Dashboards and decisions

Lesson 1 of 5 · reading 15–25 minutes; practice and project time is on the module page

Start from the decision

🎯You'll be able to

Turn a request into the decisions a dashboard supports, choose a few metrics for them, and define each metric so everyone means the same thing.

🏠The everyday picture

A car's dashboard shows speed, fuel and warning lights, because those are what a driver acts on. It doesn't show the engine's oil pressure history, though the car measures it.

📘What it really is

📝A worked example

Input: compare the starter's and the solution's dashboards (python dashboard/build.py in each, then open dashboard/out/index.html).

Expected output: the starter says "SabziSathi is growing fast!" and shows "Revenue ₹2,366,966" and "3,476 orders" with no definitions. That figure includes cancelled and refunded orders, repeated rows and staff test orders. The solution shows net revenue ₹19,65,764, 2,918 delivered orders and an average of ₹673.67, each defined under "What the numbers mean".

🌍Where it's used

📝Case scenario

Two departments of a state government each reported "beneficiaries reached" for the same scheme, 4.1 lakh and 3.2 lakh. One counted payments, the other counted people. A shared definition, printed on both dashboards, ended a month of meetings about which figure was right.

🖱️Try it

Write a one-paragraph brief for SabziSathi's store-manager dashboard: who, what decision, how often, and three metrics with definitions. Success: each metric is tied to a decision a manager makes.

⚠️Common mistakes

🛠️For your project

Project 3 tests 2 and 3 check the headline numbers and their definitions.

✅Quick check

What should a dashboard brief say?

Show the answer

Who reads it, what decision they make, and how often.

What does a metric definition include?

Show the answer

What's counted, what's left out, and the unit.

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