What the job actually is
The analyst clarifies an ambiguous question, finds and tests the relevant data, chooses appropriate calculations, communicates the result and helps the decision owner understand limitations. AI can draft queries, summaries or charts, but the analyst remains responsible for grain, filters, definitions, bias and evidence.
Translate a request into a measurable business question.
Query, clean, compare and test alternative explanations.
Create reusable measures and governed semantic definitions.
Deliver a clear visual and decision-oriented narrative.
Competency progression
| Area | Entry | Working | Advanced |
|---|---|---|---|
| SQL | Filters, joins, aggregates | CTEs, windows, debugging | Performance and complex analytical patterns |
| Analysis | Descriptive summaries | Segmentation, tests, uncertainty | Experiment and causal judgment |
| Power BI | Visuals and basic model | Star schema, DAX, RLS | Governed semantic models and performance |
| AI use | Draft and explain | Validate queries and insights | Design governed analyst workflows/data agents |
| Communication | Describe a chart | Recommend with caveats | Influence decisions across stakeholders |
Portfolio evidence
Publish a business brief, source-quality notes, reproducible SQL, a semantic model, a focused dashboard and a one-page decision memo. Add an AI validation log showing prompts or generated work, checks performed, corrections and limitations.
Typical interview loop
Progression
- Data Analyst → Senior Analyst → Analytics Lead
- Data Analyst → BI Developer or Analytics Engineer
- Data Analyst → Product Analyst, Data Scientist or AI Analytics Specialist
Responsibilities and tool stacks vary by employer. No salary or placement outcome is implied. Last reviewed 12 August 2026.