Which questions should you ask when scoping a data analytics project?

• A. Identify business objectives, required data sources, data quality, timelines, stakeholders, success metrics, and constraints.
• B. Only focus on the technology stack and ignore business goals.
• C. Start with data visualization preferences.
• D. Skip stakeholder involvement to save time.

Answer: (A)

At the heart of scoping a data analytics project is clarifying what the business aims to achieve and what will be delivered. Asking about business objectives ensures the project solves a real problem and provides value. Identifying required data sources and data quality upfront helps determine feasibility and what data preparation will be needed. Outlining timelines and milestones sets expectations and guides resource planning, while defining success metrics gives a concrete way to judge whether the project delivers the intended impact. Involving stakeholders ensures alignment across the organization and secures buy-in, and noting constraints such as budget, regulatory requirements, privacy considerations, and technical limits keeps the scope realistic and manageable.

Focusing only on the technology stack ignores the purpose and value of the work. Starting with data visualization preferences can bias the project toward presentation decisions before understanding data and requirements. Skipping stakeholder involvement leads to misaligned needs and potential resistance later on.