Data Cleaning and Quality Validation in SQL Questions
Handle NULL values, duplicates, and data type issues within queries. Implement data validation checks (row counts, value distributions, date ranges). Practice identifying and documenting data quality issues that impact analysis reliability.
HardTechnical
90 practiced
Define a set of KPIs for data quality in a product analytics platform (examples: timely-load-rate, row-reconciliation-failures, schema-drift-rate, critical-null-rate). For each KPI, state how you would calculate it in SQL, acceptable thresholds, and how to operationalize into dashboards, SLAs, and team responsibilities.
MediumTechnical
85 practiced
You have 'source_events' and 'warehouse_events' tables. Build a SQL query that performs a reconciliation check by date and event_type: compute source_count, warehouse_count, difference, and percent_difference, and flag rows where absolute percent_difference > 1%. Provide the query and explain how you would schedule and alert on such mismatches in a production pipeline.
HardSystem Design
93 practiced
Design a validation architecture for streaming data that flows from Kafka to a data warehouse. Requirements: near-real-time deduplication, detection of schema drift, handling late-arriving events, and alerting. Describe components (stream processors, schema registry, validation service), what checks run in-stream vs in-batch, and trade-offs between latency and validation depth.
HardTechnical
89 practiced
Your data-quality suite of SQL queries takes several hours and blocks nightly pipelines. Propose SQL and architectural strategies to optimize runtime: consider materialized views, incremental validation tables, sampling, approximate algorithms, partition pruning, and where to trade accuracy for speed. Provide example SQL snippets or pseudo-SQL for key optimizations.
MediumTechnical
93 practiced
You ingest a 'status' column from multiple sources and find inconsistent enum values like 'active', 'Active', 'ACT', '1'. Write SQL to join the dataset to a canonical_lookup table to normalize status codes, and produce a report of unmapped values and their counts to help expand the lookup table.
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