mdm-and-federated-data-governance
Apply Master Data Management (MDM) styles (Consolidation, Registry, Centralized, Coexistence), federated governance via data contracts and policy automation, data catalog + metalake architecture, knowledge graphs for metadata, semantic layers, and access control models (ACL, RBAC, ABAC + PEP/PDP/PIP/PAP). Use when scoping MDM, choosing an MDM style, designing a data catalog, building governance automation, defining data contracts, or implementing fine-grained access control on data products. Triggers: "MDM strategy", "consolidation vs registry vs centralized vs coexistence", "data contract", "data catalog", "knowledge graph for metadata", "ABAC for data", "semantic layer for governance", "metalake". Produces a chosen MDM style + governance architecture with policy automation.
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knowledge-graph-applications
Apply knowledge graph patterns for real applications: identity resolution (strong vs weak identifiers, Connected Components, SIMILAR), fraud detection (fraud rings, legitimate households), organizational graphs (org charts, expertise/skills graphs), dependency analysis (chains, multidependencies, redundant, SPOF, root cause), entity-based search, document similarity, and natural-language query/generation. Use when solving fraud detection, organizational analytics, dependency analysis, semantic search, or natural-language interfaces over a knowledge graph. Triggers: "fraud ring detection", "expertise graph", "single point of failure analysis", "root cause analysis with graphs", "entity-based search", "semantic search", "natural language to Cypher". Produces a pattern + query approach.
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data-mesh-domain-topologies
Pick and operate the right Data Mesh domain topology — Fully Federated, Governed, Partially Federated, Hub-and-Spoke, Centralized, Source-Aligned, Consumer-Aligned, Coarse-Grained, or Value Chain-Aligned — and apply domain-driven data product principles (Golden Source, Common Driveway, data ownership rules). Use when scoping Data Mesh adoption, choosing a domain topology that fits the org, designing landing zones, defining what a "data product" means at the company, or reconciling Mesh principles with existing centralized infrastructure. Triggers: "Data Mesh adoption", "domain topology", "data product definition", "fully federated vs governed mesh", "hub-and-spoke for data", "domain landing zones", "data ownership at scale". Produces a chosen topology with rationale and a data product blueprint.
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dataops-and-modern-data-platforms
Apply DataOps practice (SLOs, monitoring, deployment discipline for data), Modern Data Stack composition, Live Data Stack patterns, Data Mesh adoption, Semantic Layer design, Reverse ETL (BLT), Analytics Engineering / Analytics- as-Code (dbt-style), and FinOps for data. Use when establishing operations for a data team, choosing a data platform pattern (MDS vs Live vs Mesh), building a semantic layer, or operationalizing analytics. Triggers: "DataOps practice", "Modern Data Stack composition", "Live Data Stack", "Data Mesh rollout", "semantic layer", "Reverse ETL", "analytics engineering", "dbt workflow", "FinOps for data", "data platform SLOs". Produces a defined ops practice + chosen platform composition with rationale.
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