DIG091A • Term 2 • Week 1 Lesson 2

Importing Real-World Data into Excel

CSV files can look like a messy wall of text. Today we turn raw data into a structured Excel table that can be cleaned, filtered and analysed.

Today’s challenge

Can you turn a messy rainfall CSV into data that a city planner could use?

messy_rainfall_data.csv
Excel → rows, columns, fields, records
Clean → Analyse → Explain

🎯 Learning Intentions

  • Acquire data from an external source and import it into Excel.
  • Model structured data by organising it into rows and columns.
  • Explain why data must be structured before analysis.

✅ Success Criteria

  • I can open a .csv file in Excel correctly.
  • I can identify fields and records.
  • I can format basic data types: text, number and date.

🚀 Why this matters

Data is useless until it is structured. Apps, websites and companies collect data all the time. Before it can help someone make decisions, it needs to be stored in a format that software can understand.

1. Raw CSV

This is what the file looks like before Excel structures it.

Year,Month,Day,Location,Rainfall_mm,Quality
2024,1,5,Brisbane ,12.5,
2024,01,06,brisbane,8.2,
2024,1,7,BRISBANE,N/A,
2024,1,08,Brisbane,15.0,Y
2024,01,9,Brisbane,7,
2024,1,10,Brisbane,13.7,

2. Excel-style table

Press the buttons to parse the CSV and find possible data problems.

🧠 Quick check: fields

Which item is a field?

🧠 Quick check: records

Which item is a record?

🧠 Quick check: CSV

CSV stands for...

🧹 Clean the rainfall data

Click each cleaning action to see what it fixes.

📊 Mini analysis preview

After cleaning, Excel can visualise rainfall values. This simple chart shows the numeric values from the sample file.

🧭 Assessment pathway

☑ Topic + Users ☑ User Stories ✅ Data Acquisition ✅ Data Cleaning ☐ Data Analysis ☐ SQL Queries ☐ Report Writing

The assessment later asks you to submit your original CSV, cleaned Excel file and short report with analysis and SQL/query evidence.

Exit ticket

What decision could your user make from this data once it has been cleaned?

Curriculum links

AC9TDI10P01 acquire, store and validate data; AC9TDI10P02 analyse and visualise data to identify trends and outliers; AC9TDI10P04 connect real-world problems to users and user stories; AC9TDI10K02 separate webpage content, structure and presentation.