Enterprise architecture is not industry-neutral. Framework requirements, regulatory constraints, technology patterns, and organizational dynamics vary significantly by sector. A government agency running FEAF and a bank running BIAN are solving different problems with different constraints: the tooling may overlap, but the practice does not. These guides address Sparx EA practice through the lens of each industry: not generic EA theory recycled across verticals.
Key Takeaways
Government EA programs operate under FEAF (Federal Enterprise Architecture Framework) and TOGAF at the federal level, with DoDAF governing national security and defense-adjacent programs. IT modernization is the dominant program type: legacy application rationalization, cloud migration, and cross-agency data sharing. FedRAMP compliance constrains AI integration options: Azure OpenAI is the standard path for cloud AI in government contexts; the most sensitive environments require on-premises model deployment. State and local government programs follow analogous frameworks with different legislative mandates. The challenge common to all: repositories accumulated across multiple contractors and program cycles with inconsistent MDG governance.
Government and Public Sector EA Guide →
Defense organizations run some of the most complex Sparx EA deployments in existence: DoDAF 2.0 for capability and operational views, SysML for systems engineering models, and both in a single repository with traceability across acquisition program phases. CMMC compliance governs how Controlled Unclassified Information (CUI) in the EA repository can be handled and where it can flow. AI integration requires Azure Government Cloud (FedRAMP High / IL4/IL5) or on-premises deployment for classified environments. Requirements traceability from stakeholder need to system specification to test case is a primary value driver: particularly during milestone reviews.
Defense Architecture EA Guide →
Banks, insurers, and capital markets firms use Sparx EA for BIAN-aligned capability architecture, DORA compliance documentation, application portfolio management at scale, and data architecture governance for CDO mandates. DORA Article 28 third-party risk requirements affect which AI APIs can access EA repository data: Azure OpenAI or Kernaro AI Hub (configurable data residency) are the compliant paths for European institutions. Application portfolios in banking routinely exceed 1,000 systems; scale and MDG consistency are not optional. BCBS 239 data lineage requirements make the EA repository a compliance artefact, not just an architecture tool.
Healthcare EA is dominated by systems integration architecture: HL7 v2 message flows, FHIR resource profiles, integration engine topology, and the interface landscape connecting EPR/EHR systems to departmental clinical applications. Migration programs (EPR consolidation, national program participation) require AS-IS to TO-BE traceability that Sparx EA handles through its repository structure. In the UK, NHS Integrated Care System programs and ICB architecture add a layer of shared architecture governance. AI integration data governance is nuanced: architecture data about clinical systems is not PHI, but proximity to patient data systems requires classification review before connecting to any AI tool.
Telco EA programs are anchored to TM Forum Open Digital Architecture (ODA): the 325+ component model that provides the capability reference for modern telecommunications enterprises. BSS/OSS transformation is the dominant program type: rationalizing legacy stacks, migrating to microservice-based architectures, and building the product catalog and service fulfillment capabilities digital services require. 5G Core network architecture documentation (network functions, service-based interfaces, RAN topology, network slicing) in Sparx EA adds a network engineering dimension absent from most enterprise EA programs. Multi-jurisdiction operations make data residency review mandatory for any cloud AI integration.
Manufacturing EA sits at the intersection of product lifecycle management, OT/IT integration, and Industry 4.0 capability planning. The AS-IS landscape typically includes legacy PLM systems (Teamcenter, Windchill, ENOVIA), fragmented OT architectures across plant floors, and limited integration between engineering and enterprise systems. SysML is relevant here for product systems engineering; ArchiMate handles the enterprise layer; the integration between them is the practice challenge. Smart manufacturing and digital twin programs require architecture governance that most manufacturing EA practices are not yet equipped to provide.
Aerospace EA is defined by a characteristic that separates it from almost every other EA context: the systems it produces must not fail catastrophically. DO-178C governs avionics software, DO-254 governs hardware, and AS9100 governs quality management for programs subject to FAA, EASA, or defense airworthiness authority certification. Model-Based Systems Engineering in Sparx EA provides SysML with full requirements traceability from stakeholder need through design to certification evidence: the audit trail certification authorities require, not optional documentation. Defense aerospace programs combine MBSE with DoDAF or NAFv4 for capability and operational architecture, with CMMC governing how Controlled Unclassified Information in the repository is handled across the contractor supply chain.
Aerospace and Defense EA Guide →
Energy and utilities organizations are navigating OT/IT convergence alongside smart grid rollout, renewable energy integration, and regulatory compliance under NERC CIP, NIS2, and grid modernisation mandates simultaneously. Sparx EA supports ArchiMate for enterprise layer modeling, SysML for OT system specification, requirements management for ISA/IEC 62443 control traceability, and the Common Information Model (CIM) for grid data exchange architecture: all in a single governed repository. EA GraphLink connects the repository to Power BI for compliance dashboards covering CIP asset classification, NIS2 control coverage, and OT/IT integration landscapes that refresh automatically as architects update the model.
Energy and Utilities EA Guide →
Every industry has different MDG baseline conditions, different framework requirements, and different AI integration constraints. A Discover engagement scopes your practice against the specific benchmarks that matter for your sector: not a generic EA maturity model.
Discover: $25K–$75K: MDG readiness assessment, maturity baseline, AI integration feasibility scoped to your industry context.
Talk to a Sparx Services architect about where your organization is on the journey and what the next stage looks like.