Module 10 · Data Analytics Foundations
Your first analytics project
Run the whole cycle on Kolanut's staff data, from question to recommendation, and prepare for the final project.
About 40 minutes
The problem
Kolanut's HR manager is worried: "It feels like we keep losing people, especially in customer service. Is that true, and what should we do?"
This lesson walks through a small but complete analysis of that question. The course's final project then asks you to take it further on your own.
The concept
A complete analysis, even a small one, has five parts. You'll produce them for the final project:
- The question, in measurable form.
- The data you used and anything you cleaned or excluded.
- The analysis: the calculations and a chart or table.
- The finding, in one or two sentences.
- The recommendation and its limits: what the data can't tell you.
A note on small numbers. Kolanut has 80 employees. When you split them by department, some groups have only 6 or 8 people. One resignation in a group of 8 moves the rate by 12.5 percentage points. Report the counts next to the rates, and be careful about strong conclusions from small groups.
Example
Question. Of everyone Kolanut has employed since 2018, what share has resigned, and does it differ by department?
Data. employees.csv: one row per employee, with department, job_level and status (Active or Resigned).
Analysis.
| Department | Staff | Resigned | Resigned % |
|---|---|---|---|
| Customer Service | 8 | 3 | 37.5% |
| Finance | 10 | 2 | 20.0% |
| Operations | 27 | 5 | 18.5% |
| IT | 12 | 1 | 8.3% |
| Sales | 17 | 0 | 0.0% |
| Human Resources | 6 | 0 | 0.0% |
| All | 80 | 11 | 13.8% |
Finding. Customer Service has the highest share of resignations (3 of 8 people, 37.5%), about three times the company-wide rate. By job level, all 11 people who left were Junior or Mid level; no Senior staff or Managers resigned.
Recommendation. Hold short exit and "stay" conversations with Customer Service staff to understand why people leave, and review junior pay and workload there. Limit: these are small numbers, and the data has no reasons for leaving, so treat this as a signal to investigate, not proof.
Walkthrough
How to produce the table above in a spreadsheet:
- Open
employees.csvin Google Sheets or Excel. - Insert a pivot table (Sheets: Insert → Pivot table; Excel: Insert → PivotTable).
- Put
departmentin Rows. - Put
employee_idin Values, summarised by COUNTA (Sheets) or Count (Excel). That's the Staff column. - Put
statusin Columns. You now have Active and Resigned counts per department. - Next to the pivot, calculate Resigned ÷ Staff × 100 for each department.
- Sort by the percentage, largest first.
Practice
Practice
Across all 80 employees, what percentage have resigned? Give one decimal place.
Practice
Now attendance. In attendance.csv (June 2026, active staff only), how many records have the status Late?
Check your understanding
Answer every question to check.
When you've finished this lesson, take the final assessment, then open the final project from the course page.