Architecture and Technical Trade Offs Questions

Centers on system and solution design decisions and the trade offs inherent in architecture choices. Candidates should be able to identify alternatives, clarify constraints such as scale cost and team capability, and articulate trade offs like consistency versus availability, latency versus throughput, simplicity versus extensibility, monolith versus microservices, synchronous versus asynchronous patterns, database selection, caching strategies, and operational complexity. This topic covers methods for quantifying or qualitatively evaluating impacts, prototyping and measuring performance, planning incremental migrations, documenting decisions, and proposing mitigation and monitoring plans to manage risk and maintainability.

MediumTechnical

0 practiced

As a BI team lead with limited engineering support, how would you prioritize technical debt items such as slow dashboards, flaky refresh jobs, and inconsistent KPIs? Describe a prioritization framework that balances business impact, effort, risk, and strategic value and explain how to get stakeholder buy-in for the chosen priorities.

EasyTechnical

0 practiced

Define Service Level Agreements (SLA) and Service Level Objectives (SLO) and explain how you'd apply them to a BI reporting system. Provide concrete examples such as an SLO for dashboard load time (e.g., p95 < 2s), an SLO for data freshness, and an SLA-level commitment to a business unit. Describe how you'd monitor and enforce these promises.

EasyTechnical

0 practiced

How would you quantify the business impact and incremental infrastructure cost of increasing dashboard refresh frequency from once per day to once per hour? List the data points you would collect, outline a simple cost model for compute/network, and describe how you would translate predicted user behavior changes into economic value for stakeholders.

HardSystem Design

0 practiced

Design a telemetry and observability framework for a BI platform to detect regressions such as increased query latency, incorrect aggregates, and stale data. Specify key metrics, logs, distributed tracing points, dashboards for SREs and analysts, alerting rules, and examples of automated remediations you might implement.

HardTechnical

0 practiced

Develop a quantitative model to estimate the change in infrastructure cost and query latency when reducing dashboard refresh interval from 60 minutes to 1 minute across a fleet of 200 dashboards. Describe assumptions, variables (compute per query, concurrency, cache reuse), and how you'd validate the model with a pilot. Provide example calculations or formulas you would use.

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