Focuses on establishing, communicating, and enforcing team and cross team processes that ensure consistent technical quality. Topics include coding standards and style guides, code review policies and workflows, branch and release strategies, continuous integration and continuous delivery pipelines, static analysis and linting toolchains, automated quality gates and pre commit checks, integration of testing into pipelines, metrics for defect rates complexity and coverage, strategies to manage technical debt and legacy code, governance models for exceptions and escalation, and balancing standard strictness with developer productivity. Interviewers look for experience designing standards, driving adoption, integrating tool chains, and measuring impact.
EasyTechnical
0 practiced
What should a code review policy for BI artifacts include to ensure consistent technical quality while enabling analysts to move fast? Describe concrete rules (e.g., required reviewers, checklist items for dashboards, SQL style checks, rollback plan) and how you would enforce the policy in a Git-based workflow.
MediumTechnical
0 practiced
How would you measure technical debt and the legacy-report backlog in a BI environment? Propose concrete metrics (for example, age distribution, maintenance effort, duplication rate, coverage gaps), how to collect them programmatically, and thresholds to prioritize remediation work.
MediumTechnical
0 practiced
Design a composite metric called report reliability that combines dataset freshness SLA compliance, number of data accuracy incidents in the last 90 days, and visual rendering errors. Describe how to normalize components, weight them, set thresholds, and how you would display this score to different stakeholders.
EasyTechnical
0 practiced
Define CI/CD in the context of BI artifacts such as dashboards, shared datasets, LookML models, Power BI reports, and ETL jobs. Explain why automated build, test, and deployment pipelines matter for BI delivery, reproducibility, compliance, and cross-team collaboration. Give two concrete examples of failures CI/CD would prevent.
MediumSystem Design
0 practiced
Design a CI/CD pipeline for Power BI artifacts that supports dev, qa, and prod promotion of datasets (dataflows), shared datasets, and report files (.pbix). Include artifact versioning, automated data and visual tests, approvals, rollback strategy, and workspace/permission considerations. Describe the components and their interactions.
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