U02A — The data analyst role
U02A — The data analyst role
What analysts do day to day, the skills they need, and how the role differs from BI, engineering, and data science.
By the end of U02A, you will be able to:
- Describe a typical analyst week (not a fixed job description).
- Name the three skill pillars of a strong analyst.
- Contrast the analyst with BI, engineer, and scientist roles.
- Recognize tasks that belong to the analyst vs tasks that belong elsewhere.
1. What is a data analyst?
A data analyst turns business questions into evidence-based answers. You sit between people who decide and the data that should inform those decisions. Your output is not “more data” — it is clarity: what happened, why it might matter, and what to do next.
- ~25% — Meetings & clarifying requests (“What decision do you need?”)
- ~30% — Finding, exporting, and checking data quality
- ~25% — Exploring numbers, comparisons, exceptions
- ~15% — Charts, slides, short written summaries
- ~5% — Follow-up: did the decision work? What changed?
Analysts rarely spend 100% of the day in one tool. You might use spreadsheets, exports from a CRM, a BI dashboard, or a SQL query someone prepared for you. The constant is the question → evidence → recommendation loop.
2. Three skill pillars
3. Analyst vs nearby roles
| Role | Primary focus | Example task | How you work together |
|---|---|---|---|
| Data analyst (you) | Ad-hoc questions → analysis → recommendations | “Why did returns spike in March?” | Owns the full question-to-answer path for one-off decisions |
| BI analyst | Dashboards, KPIs, ongoing monitoring | Weekly revenue dashboard refresh | May share trusted metrics; you dig deeper when the dashboard raises a “why” |
| Data engineer | Pipelines, databases, reliable data flow | Nightly sync from shop POS to warehouse DB | Builds access; you consume clean tables or exports |
| Data scientist | Models, experiments, advanced statistics | Churn prediction model | Partners on complex prediction; you may prepare features or explain results to business |
4. What analysts usually do not own
- Designing company logos or brand guidelines
- Building and maintaining production ETL pipelines (engineer territory)
- Training deep learning models as a daily job (scientist territory)
- Replacing legal, HR, or finance judgment — you inform decisions, stakeholders decide
U01C introduced these role names at a high level. U02A goes deeper on the analyst only. U02B covers the repeatable workflow you will use on every assignment.
Ready? Take the U02A quiz on this page
5 questions · 100% correct required to complete this lesson
Wrong answers show a hint — review the lesson and try again.
When you pass → continue to U02B — The six-stage analyst workflow
What analysts do day to day and the six-stage workflow from business question to actionable answer.
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