# Data Stack **Domain:** Software Engineering, Data Science, Technology Architecture **Doc Type:** Concept Node **Classification:** Infrastructure Concept **Maturity:** Foundational **Related:** [[Data Infrastructure]], [[Data Platforms]], [[Computational Architecture]], [[Digital Administrative Infrastructure]] --- ## Definition The **layered set of technological components and tools—from sensors through storage, processing, analysis, visualization, and delivery—that together enable data-driven operations**. The stack specifies how data flows from collection through use. --- ## General Context A data stack includes sensors (data source), networks (transmission), storage systems (databases), processing (computing), analysis tools (algorithms), and visualization (output). Modern stacks are increasingly cloud-based and modular. --- ## Governance Context Governance data stacks integrate environmental sensors, forecasting models, financial data, and decision support systems. Stack architecture determines governance feasibility. --- ## Computational Governance Context Modern governance stacks are increasingly cloud-based, introducing third-party infrastructure providers (AWS, Google Cloud) as governance participants. --- ## Key Insight The data stack architecture determines what latencies are acceptable, what kinds of processing are feasible, and who can access data at which stages. Choices that appear technical embed governance implications. --- ## See Also [[Data Assimilation]], [[Sensing]], [[Computational Process]]