Automated Reporting & Report Development Questions
Build automated reports that refresh on schedule. Understand refresh schedules, data pipeline integration, and deployment to production. Create parameterized reports for different stakeholder needs. Know how to version control and manage report changes.
MediumTechnical
0 practiced
Given a staging table staging_orders(order_id INT, status VARCHAR, updated_at TIMESTAMP) and target analytics table orders(order_id INT PRIMARY KEY, status VARCHAR, updated_at TIMESTAMP, is_latest BOOLEAN), write an ANSI SQL MERGE statement (or equivalent) to upsert rows from staging into orders: insert new rows, update changed rows, and set is_latest appropriately. Include logic to mark previous rows as not latest if needed.
MediumTechnical
0 practiced
Design an automated report framework that serves three stakeholder groups with different needs: executives (high-level KPIs refreshed daily), product managers (feature-level metrics with filters refreshed hourly), and analysts (ad-hoc data access). Explain your choices for data modeling, semantic layer, parameterization, refresh cadence, and access controls.
MediumTechnical
0 practiced
Explain how Power BI incremental refresh works: the role of range start/end parameters, how partitions are created, how changed partitions are detected and processed, how incremental refresh reduces load, and common limitations or gotchas you should be aware of.
HardSystem Design
0 practiced
Design an automated reporting pipeline for daily A/B test dashboards: ingest experiment events and assignment records, join exposures to outcomes, compute per-metric lifts with confidence intervals, and publish summarized dashboards. Address data correctness, which statistical test you would use, how to handle unbalanced samples and early stopping, and how to alert when tests meet pre-defined criteria.
HardTechnical
0 practiced
Propose an implementation for end-to-end data lineage and report versioning so that an analyst can trace a dashboard metric back to the specific source tables and ETL job runs that produced it. Include metadata model, where to store lineage info, instrumentation points in pipelines, and how to expose lineage to users.
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