Business Objective Alignment & Value Creation Questions
Ability to connect transformation initiatives to business objectives and organizational strategy. Understanding that technology is an enabler for business goals, not an end in itself. Knowing transformation investments should deliver measurable business value and competitive advantage aligned with strategy.
HardTechnical
0 practiced
Leadership/case: Build an outline for a business-case presentation to justify migrating BI to a modern cloud data platform (for example, Snowflake + Looker). Include KPIs to show success, a cost model (including migration costs and ongoing costs), expected benefits (time-to-insight, reduced maintenance), risks, and a phased migration plan with measurable milestones.
EasyTechnical
0 practiced
You are given the company's top-level OKRs for the quarter. Describe step-by-step how you would translate OKRs into prioritized dashboard requirements for executive leadership. Include how you would decide which KPIs require near-real-time reporting versus daily or weekly, and how you would capture assumptions and owners.
EasyTechnical
0 practiced
Theoretical: Why is it important for BI initiatives to be explicitly mapped to business objectives? Provide examples of two transformation projects where technology could be mistaken for value and explain how you would prevent that in measurement design.
MediumTechnical
0 practiced
SQL task (ANSI SQL): Given a subscriptions table below, write a query to calculate month-over-month percentage change in MRR (monthly recurring revenue) for the last 12 months and flag months where change > 10%.Schema:subscriptions(subscription_id, customer_id, monthly_amount numeric, start_date date, end_date date NULLABLE)Return: month_start, mrr, pct_change, is_large_change boolean. Explain assumptions about proration and canceled subscriptions.
HardTechnical
0 practiced
Operational case: The sales team requests a daily forecast of deal closures tied to quarterly revenue OKRs. Describe model features you would include, how you'd evaluate forecast accuracy, how you'd align the forecast to OKRs (e.g., probability-weighted vs conservative), and how to present uncertainty to stakeholders.
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