How to Avoid Accuracy Challenges in Ad Hoc Reporting
Blog post from Sigma
Ad hoc reporting can produce inaccurate results when teams rely on exported files, use inconsistent metric definitions, or distribute manually prepared analyses without adequate validation, potentially causing errors in high-stakes decisions. The recommended approach is to query governed cloud warehouse data directly, centralize key business metrics in a semantic layer, document lineage, and incorporate checks for filters, joins, outliers, and trusted benchmarks before reports are shared. For sensitive or executive-facing outputs, peer review, version history, and timestamps can improve traceability and accountability, while warehouse-enforced row-level security, shared metric catalogs, and automated refreshes reduce reliance on manual processes. The piece presents Sigma as a warehouse-native analytics platform that executes queries on live cloud data, inherits warehouse security controls, and integrates with semantic layers such as Snowflake Semantic Views and dbt to help ad hoc reports, dashboards, and formal reporting use consistent governed data.
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