Business Intelligence and Reporting Infrastructure Questions

Building and operating reporting and business intelligence infrastructure that supports dashboards, automated reporting, and ad hoc analysis. Candidates should discuss data pipelines and extract transform load processes, data warehousing and schema choices, streaming versus batch reporting, latency and freshness trade offs for real time reporting, dashboard design for different audiences such as individual contributors managers and executives, visualization best practices, data validation and quality assurance, monitoring and alerting for reporting reliability, and governance concerns including access controls and privacy when exposing data.

MediumTechnical

0 practiced

Design a retention policy for raw events, intermediate transformed datasets, and aggregated metrics to balance compliance, cost, and analytical needs. Explain retention windows, cold storage options, and methods to reconstruct aggregates if raw events are truncated.

MediumTechnical

0 practiced

Describe how you would implement and use time travel or versioned datasets (if supported) to debug and validate historical dashboards. Include examples of queries to compare versions and how to expose version metadata to analysts.

HardTechnical

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Design a rollback and auditing strategy for accidental mass-deletes that affected production reporting tables. Include how to detect the deletion, restore data from backups or change logs, validate restored values, and communicate impact to stakeholders.

HardTechnical

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Propose a comprehensive data validation and automated testing strategy for ETL pipelines feeding BI reports. Include types of tests (unit, integration, regression), sample assertions, synthetic test data use, and how to integrate tests into CI/CD.

EasyTechnical

0 practiced

Explain columnar storage vs row-oriented storage. As a BI analyst, when would you prefer a columnar store for analytics workloads? Discuss compression, IO patterns, and impact on aggregation queries.

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