Translating Business Problems to Computational Solutions Questions
Techniques and practices for analyzing business problems, defining success criteria, and translating them into concrete computational requirements, features, user stories, and architectural decisions. Aligns business goals with product strategy, roadmap, and delivery plans; emphasizes stakeholder collaboration, scoping, prioritization, and value-driven thinking.
HardTechnical
0 practiced
Create a technical plan to quantify and reduce 'cost of delay' for a product roadmap of 8 candidate features over 12 months. Include required data inputs, a Monte Carlo approach (or simpler model) to estimate expected lost value, a prioritization algorithm, and how results are communicated to executives.
HardSystem Design
0 practiced
You must integrate a mission-critical legacy ERP into a cloud-native microservices platform without downtime. Design a phased migration plan including data synchronization approaches, transaction integrity guarantees, reconciliation processes, and monitoring strategy for cutover readiness.
EasyTechnical
0 practiced
List the top five deliverables (artifacts) you would produce to translate a customer's business problem into a technical solution during pre-sales. For each deliverable explain its audience (technical/executive), purpose, and an example one-line content sample.
MediumTechnical
0 practiced
As a Solutions Architect, create a comparative TCO analysis outline for 'build custom search' vs 'use managed SaaS search'. List the cost categories, risk factors, and show an example table of one-year vs three-year costs and qualitative trade-offs you'd present to the customer.
MediumTechnical
0 practiced
Translate the business request 'personalize product recommendations' into a technical specification: data sources required, offline feature engineering pipeline, online feature serving, model choice constraints (latency, freshness), and success metrics to evaluate recommendations in production.
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