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PROFESSION PREPARATION ROUTE
A preparation file for data analysis
Prepare examples showing the question you answer, data-cleaning choices and the limits of findings.
Research from the listing
- Separate reporting, analysis and data-preparation tasks.
- Ask how named tools relate to expected outputs.
- Write questions about data source, update frequency and audience.
Your evidence
- Explain why you chose a dataset and what it does not represent.
- Record decisions about missing or repeated rows instead of silently deleting them.
- Separate findings from interpretation; sample data cannot establish an industry-wide result.
Interview explanations
- How would you explain a table to a non-technical reader?
- What would you ask first about an undefined metric?
- Which assumption would you recheck if the same data produced a different conclusion?
This week’s concrete file
- Use fictional support data to prepare one question and a small summary.
- Add two cleaning decisions and one limitation to a case note.
- Label the work an exercise rather than a real client outcome.
AN EXERCISE IN THIS FIELD
Practise with a project brief.
A fictional sample CSV, four work steps and a place to save your own draft.
Open sample project ↗Research the occupation at the source
This link describes an occupation in the United Kingdom. Roamwise authored the exercises here; the source does not establish training, authorisation or permission requirements in other destinations.
National Careers Service · Data analyst-statistician ↗Link checked: 2026-10-24
This is a research and preparation worksheet. Verify professional authorisation, language documentation and destination requirements with the relevant authority. It does not rank demand, salaries or hiring probabilities.