What you do in this role

Clarify what a stakeholder means by growth, retention or revenue. Extract and clean records, establish the correct reporting grain, compare segments and communicate uncertainty. A useful deliverable combines a reproducible query, a small chart and a recommendation with limitations. Expect time spent checking definitions and discussing the result, not only writing code.

Tools and how to use them

These are example choices, not a requirement to learn or purchase every product.

Where AI helps—and what you must verify

Use an approved AI assistant to suggest exploratory questions, explain unfamiliar SQL and draft a summary. Give it a schema and synthetic examples, then independently check joins, denominators and dates. Gemini in BigQuery provides SQL and Python assistance; tool access depends on the organisation. AI can accelerate a first draft, but it cannot establish causality from a simple correlation.

Use only tools approved for the data involved. Keep confidential records and credentials out of unapproved prompts. Save enough of the reasoning, tests and assumptions for another person to reproduce the result.

A portfolio project you can explain

Investigate a synthetic subscription business where monthly revenue falls from $12,000 to $10,800. The decline is $1,200, or 10%. Separate customer count, average price and refunds before proposing a cause. Deliver an SQL query, a reconciliation sheet, three charts and a one-page decision memo. State what evidence is missing, such as campaign exposure or plan changes.

Use synthetic or appropriately licensed data. Include a README, data dictionary, reproducible steps, expected results and one deliberate failure case. Describe what you personally built and distinguish a practice project from paid client work.

A four-stage learning path

Move forward when you can explain and reproduce the result. These stages are not a job-placement timetable.

1. Define a metric and solve filtering, joins and aggregation exercises. Explain the grain of every table.
2. Clean one messy CSV, document rejected records and reconcile the cleaned total to the input.
3. Build one dashboard answering a specific business question; test its filters and refresh date.
4. Present the project in five minutes and answer follow-up questions without reading a script.

Interview and mock-practice prompts

• Why did revenue fall while order count increased?
• How can a join inflate a total, and how would you catch it?
• When would a median be more useful than a mean?

Structure an answer around the requirement, assumptions, approach, validation and tradeoffs. For a practice session, spend five minutes clarifying the problem, fifteen solving it and ten explaining tests and alternatives. This is a suggested self-practice format.

Review your answer for correctness, communication and missing checks. Keep a short improvement list, then repeat a different problem to test whether the learning transfers.

Experience and progression

An early-career analyst should be able to complete a bounded analysis with review. More experienced analysts define ambiguous metrics, influence decisions and review other people’s work. Possible directions include product analytics, analytics engineering and analytics leadership; progression depends on demonstrated scope, not a fixed number of months.

Do I need advanced machine learning?

Many analyst roles focus on SQL, business reasoning and communication. Learn statistical fundamentals first and add modelling when the target job actually requires it.

How should I compare an offer?

Ask for the base salary, variable-pay conditions, equity terms, working hours and location policy in writing. Check the actual responsibilities against the benchmark title. A higher headline amount may come with different on-call expectations or benefits.

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Technical references

• Google Cloud: Gemini in BigQuery
• Microsoft: Copilot for Power BI
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