Explores the six core architecture domains: business, capability, information, application landscape, data, and integration.
8
Business Architecture
Designing an IT landscape without understanding the business is just very confident guessing with a bigger budget.
Romano Roth & Dietmar Wettach
Learning objectives
- Distinguish business architecture from enterprise architecture and explain their complementary roles
- Describe the four key elements of business architecture: capabilities, value streams, organization, and information
- Apply the Business Model Canvas to articulate how an organization creates, delivers, and captures value
- Explain how Porter's Value Chain classifies activities into primary and support categories for investment prioritization
- Identify the bidirectional relationship between business and IT alignment, including how Conway's Law shapes architecture decisions
9
Capability Mapping
A capability map answers the one question most leadership teams can't agree on: what does this company actually do?
Romano Roth & Dietmar Wettach
Learning objectives
- Apply the three-level capability hierarchy (L1 domains, L2 planning capabilities, L3 implementation capabilities) to structure a capability map
- Evaluate capability definitions against quality criteria such as outcome orientation, stability, and abstraction consistency
- Design a capability mapping workshop using the six-step creation process described in this chapter
- Explain how capability maps link to processes, applications, and data to serve as the "Rosetta Stone" of business-IT alignment
- Apply heatmap assessments to identify strategic priorities and investment needs across a capability landscape
10
Information Architecture
A knowledge base without information architecture is just a landfill with a search box.
Romano Roth & Dietmar Wettach
Learning objectives
- Distinguish between EA-focused information architecture (business objects, CRUD matrices, data flows) and content-focused information architecture (navigation, labeling, metadata)
- Apply CRUD matrices to identify data ownership, redundancy, and integration requirements across applications
- Describe business object modeling using three granularity levels (core business objects, business objects, information objects)
- Explain how taxonomies and controlled vocabularies support information findability and governance
- Identify the key IA deliverables and their role in application landscape planning and integration design
11
Application Landscape Planning
You don't have 400 applications because you needed 400. You have them because retiring one was always someone else's problem.
Romano Roth & Dietmar Wettach
Learning objectives
- Explain the application landscape planning (Bebauungsplanung) methodology and its three fundamental goals: business alignment, pain resolution, and IT readiness
- Apply Hanschke's analysis patterns in the five categories this book abbreviates as RIOFT (Redundancies, Inconsistencies, Organizational responsibilities, Fulfillment of business requirements, Technical optimization) to assess the current application landscape
- Describe the iterative process for designing a target landscape, from establishing business context to evaluating planning scenarios
- Evaluate applications using the four-quadrant portfolio assessment framework (strategic, at risk, support, phase out)
- Classify applications by criticality level (safety, mission, business critical, non-critical) and explain how RTO and RPO metrics guide resilience planning
- Apply the TIME model (Tolerate, Invest, Migrate, Eliminate) to determine rationalization strategies for an application portfolio
- Compare big bang and evolutionary migration strategies and explain how roadmaps bridge the gap between current and target landscapes
12
Data Architecture
Everyone wants to be data-driven. Almost nobody wants to agree on what 'customer' means.
Romano Roth & Dietmar Wettach
Learning objectives
- Describe the three data architecture layers (conceptual, logical, physical) and explain which layers are the primary concern of enterprise architects
- Explain the data governance role model (Data Trustee, Data Owner, Data Steward, Data Custodian) and its organizational implications
- Explain the purpose of Master Data Management, the Golden Record concept, and the four MDM styles (registry, consolidation, coexistence, centralized)
- Compare modern data architecture patterns: Data Warehouse, Data Lake, Data Lakehouse, Data Mesh, and Data Fabric
- Apply the six data quality dimensions (accuracy, completeness, consistency, timeliness, validity, uniqueness) to assess data health
- Identify the architectural implications of AI workloads on data infrastructure, including vector databases, feature stores, and data lineage
- Explain the EA-level role of data deletion and system decommissioning, including retention policies, decommissioning discipline, and verifiable deletion
13
Integration Architecture
Ten systems wired straight to each other need forty-five connections, and every one of them was somebody's quick fix.
Romano Roth & Dietmar Wettach
Learning objectives
- Compare integration patterns (point-to-point, hub-and-spoke, event-driven, API-led, iPaaS) and evaluate their trade-offs for different scenarios
- Explain API governance principles, including API-first design, lifecycle management, and the role of API gateways
- Describe event-driven architecture patterns (event notification, event-carried state transfer, event sourcing, CQRS) and their use cases
- Distinguish between integration scenarios (A2A, B2B, B2C, IoT) and identify appropriate patterns for each
- Apply integration governance practices, including architecture review for new integrations and documentation in the EA repository