Data Approval Workflows: What They Are and How They Work

Data approval workflows are formal processes that route proposed data changes to designated reviewers, capture approve, reject, revise, or escalate decisions, write approved changes back to source systems, and retain timestamped audit records. Unlike informal email, spreadsheet, or messaging-based review chains, they use role-based routing, validation, escalation rules, defined decision criteria, and traceable evidence intended to support governance, data quality, and regulatory requirements such as SOX, GDPR, and HIPAA. Workflows may be linear for sequential authority, parallel for independent reviews, or conditional based on a change’s risk, type, and scope, often combining these models. Effective implementations establish clear approval hierarchies and separation of duties, build tamper-resistant audit trails from the outset, keep rules close to the underlying data, and define exception-handling paths. The piece presents Sigma as a warehouse-native platform for implementing such workflows through Input Tables, Sigma Actions, audit logging, row-level security, and configurable AI agents that can assist with policy checks and human-approved actions across cloud data warehouses.

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