Enterprise Architecture Glossary of Terms

1. Enterprise Architecture (EA): An approach to organizing an organization’s structure, operations, and IT infrastructure to align with its business strategies and goals.
2. Architecture Framework: A structured methodology for creating, presenting, and managing EA, such as TOGAF, Zachman, and FEAF.
3. Business Architecture: The design of business strategy, structure, processes, and technologies to achieve organizational objectives.
4. Information Architecture: The design and organization of data and content, typically focusing on usability and findability.
5. Technology Architecture: The design and structure of technological systems, including hardware, software, and networks.
6. Application Architecture: The high-level structure of software applications, including the roles, functionalities, and interactions of application components.
7. Data Architecture: The policies, rules, and models that govern and define the type, nature, and organization of data.
8. Solution Architecture: The detailed description of an enterprise’s software, system interactions, and alignment with business goals.
9. Reference Architecture: A standard architecture structure that provides a common language, best practices, and consistency.
10. Infrastructure Architecture: The model outlining the structure and operation of an IT environment, including hardware, software, and services.
11. Software Architecture: The process of defining a structured solution that meets all of the technical and operational requirements while optimizing common quality attributes like performance and security.
12. Systems Architecture: A conceptual model that defines a system’s structure, behavior, and views.
13. Cloud Architecture: The design of IT resources, services, software, and hardware that are used for cloud computing.
14. Microservices Architecture: A design principle for developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms.
15. Domain-Driven Design (DDD): An approach to software development that centers the logic and complexity at the application’s core and prioritizes continuous improvement.
16. Service Oriented Architecture (SOA): A style of software design where services are provided to the other components by application components through a communication protocol over a network.
17. Web Services: A standardized way of integrating web-based applications using open standards over an internet protocol backbone.
18. API (Application Programming Interface): A set of routines, protocols, and tools for building software and applications.
19. REST (Representational State Transfer): A software architectural style defining a set of constraints for creating web services.
20. SOAP (Simple Object Access Protocol): A messaging protocol that allows programs running on disparate operating systems to communicate.
21. Security Architecture: A blueprint for enterprise security systems that describes how the design helps protect a company’s digital and physical assets.
22. Network Architecture: The design of a computer network consisting of hardware, software, connectivity, network protocols, and mode of operation.
23. BPM (Business Process Management): The discipline of improving a business process from end to end by analyzing it, modeling how it works in different scenarios, executing improvements, monitoring the improved process, and continually optimizing it.
24. BPEL (Business Process Execution Language): An XML-based language that allows web services in a service-oriented architecture (SOA) to interconnect and share data.
25. UML (Unified Modeling Language): A standardized modeling language enabling developers to specify, visualize, construct and document artifacts of a software system.
26. BPMN (Business Process Model and Notation): A graphical representation for specifying business processes in a business process model.
27. EA Tool: Software applications that support enterprise architects and other business and IT stakeholders with strategically driven planning, analysis, design and execution.
28. Metadata: Information about other data, it describes the content, quality, condition, origin, and other data characteristics.
29. Data Modeling: A method of creating a data model for storing the data in a database. This conceptual representation of data objects, the associations between different data objects and the rules.
30. ER Diagram (Entity-Relationship Diagram): A type of data diagram showing how an entity relates to other things. It helps define relationships between entities stored in a database.
31. Use Case: A list of actions or event steps to achieve a goal, typically defining the interactions between a role and a system.
32. Sequence Diagram: A type of diagram in UML that shows object interactions arranged in time sequence, particularly focusing on the order of the interaction visually.
33. Component Diagram: A UML diagram depicting how components are wired together to form larger components or software systems.
34. Architectural Pattern: A general, reusable solution to a commonly occurring problem in software architecture within a given context.
35. Design Pattern: A reusable solution to a commonly occurring problem within a given context in software design.
36. Object-Oriented Programming (OOP): A programming paradigm based on the concept of “objects”, which can contain data and code: data in the form of fields and code in the form of procedures.
37. Functional Programming: A programming paradigm where programs are constructed by applying and composing functions, avoiding mutable data and the side effects of other programming paradigms.
38. Imperative Programming: A programming paradigm that uses statements that change a program’s state, focusing on describing how a program operates.
39. Declarative Programming: A programming paradigm that expresses the logic of a computation without describing its control flow, focusing on describing what the program must accomplish.
40. Agile Development: A method for software development that emphasizes flexibility, interactivity, and a high level of customer involvement.
41. Scrum: An Agile framework for managing work with an emphasis on software development, promoting iterative progress, flexibility, customer input, and product quality.
42. DevOps: A set of practices that combines software development and IT operations, aiming to shorten the system’s development life cycle and provide continuous delivery with high software quality.
43. CI/CD (Continuous Integration/Continuous Deployment): A method to frequently deliver apps to customers by introducing automation into the stages of app development. The main concepts attributed to CI/CD are continuous integration, delivery, and deployment.
44. Serverless Architecture: A software design model where a cloud provider runs the server and dynamically manages the allocation of machine resources.
45. Containerization (e.g. Docker): A lightweight alternative to full-machine virtualization that involves encapsulating an application in a container with its own operating environment.
46. Kubernetes: An open-source platform designed to automate deploying, scaling, and operating application containers.
47. Orchestration: The automated configuration, coordination, and management of computer systems, software, and services.
48. Virtualization: Creating a virtual version of something, such as a hardware platform, operating system, storage device, or network resources.
49. Hypervisor: Software that creates and runs virtual machines (VMs) by separating the computing environment from the actual physical infrastructure.
50. IaaS (Infrastructure as a Service): A cloud computing model where a third-party provider hosts and maintains core infrastructure, including hardware, software, servers, and storage.
51. PaaS (Platform as a Service): A cloud computing model that provides a platform to customers, allowing them to develop, run, and manage applications without the complexity of building and maintaining the infrastructure.
52. SaaS (Software as a Service): A cloud computing model where a service provider hosts applications for customers and makes them available to these customers via the Internet.
53. IT Governance: The framework that ensures IT investments support business objectives.
54. IT Strategy: The comprehensive plan by which an organization aligns its IT objectives with business goals.
55. Digital Transformation: Integrating digital technology into all business areas fundamentally changes how you operate and deliver value to customers.
56. Roadmap: A strategic plan that defines a goal or desired outcome and includes the major steps or milestones needed to reach it.
57. Gap Analysis: The process of comparing an organization’s current and desired future state to identify gaps or differences.
58. Baseline Architecture: A reference structure defined for an enterprise that records its current state regarding business processes, information systems, and technologies.
59. Target Architecture: The description of the future state of the architecture being developed for an organization.
60. Transition Architecture: The architecture between the baseline and target architectures represents the changes needed to achieve the future state.
61. Architecture Vision: A brief description of the future state of the architecture for a particular domain or solution that provides the target for governance activities and a context for making architectural decisions.
62. Stakeholder: Any person, organization, or entity that has a stake in the outcome of a decision, process, or project.
63. Business Strategy: The means by which an organization sets out to achieve its desired objectives or end goals.
64. Strategic Alignment: The process of ensuring that all aspects of a company’s operations, including IT, support accomplishing its overall strategic goals.
65. Enterprise Continuum: A framework in TOGAF that provides a view of the Architecture Repository that shows the relationships among the reference models, architectures, and solutions within it.
66. ADM (Architecture Development Method): A method for developing enterprise architecture and forms the core of TOGAF.
67. ITIL (Information Technology Infrastructure Library): A set of detailed practices for IT service management that focuses on aligning IT services with business needs.
68. Portfolio Management: The centralized management of one or more portfolios to achieve strategic objectives.
69. Program Management: The coordinated management of related projects, which may include an ongoing process, a service provision, or a change to organizational structure or cultural change.
70. Project Management: The practice of initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria at the specified time.
71. Risk Management: The identification, assessment, and prioritization of risks followed by coordinated and economical application of resources to minimize, monitor, and control the probability or impact of unfortunate events.
72. Requirements Management: The process of collecting, analyzing, defining, and documenting requirements and ensuring everything is communicated to stakeholders and used for project execution.
73. SDLC (Software Development Life Cycle): A process the software industry uses to design, develop and test high-quality software. It consists of a detailed plan describing developing, maintaining, replacing, and altering or enhancing specific software.
74. MVP (Minimum Viable Product): A version of a product with just enough features to be usable by early customers who can then provide feedback for future product development.
75. Value Stream: An organization’s activities to deliver a product or service to its customers.
76. IT Service Management (ITSM): A set of policies and practices for implementing, managing, and delivering IT services to meet the needs of an organization.
77. Change Management: The process, tools, and techniques to manage the people side of change to achieve the required business outcome.
78. Capability: The ability of an organization to perform a certain activity. In the context of EA, a capability often refers to the business’s ability to deliver value to customers.
79. Business Function: A part of a business that is responsible for specific outcomes, outputs, or results.
80. Business Process: A series of steps performed by a group of stakeholders to achieve a concrete goal.
81. Business Model: A company’s plan for how it generates, delivers, and captures value in economic, social, cultural or other contexts.
82. Business Capability: A specific ability a business has, usually defined in terms of what the business does or can do strategically.
83. IT Asset: Any data, device, or other environment component supporting information-related activities.
84. IT Infrastructure: The composite hardware, software, network resources, and services required for the existence, operation, and management of an enterprise IT environment.
85. Microservices: A specific method of developing software systems that focuses on building single-function modules with well-defined interfaces and operations.
86. Monolithic Architecture: A software development pattern where an application is built as one unit. All code for different modules runs in the same process, allowing for tight coupling of services and resources.
87. Data Lake: A storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured, and unstructured data.
88. Big Data: A term for data sets that are so large or complex that traditional data processing applications are inadequate to deal with them.
89. Data Warehouse: A system used for reporting and data analysis, considered a core business intelligence component.
90. Business Intelligence (BI): A technology-driven process for analyzing data and presenting actionable information to help executives, managers, and other end users make informed business decisions.
91. Machine Learning: A type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed.
92. Artificial Intelligence (AI): A branch of computer science that aims to imbue software with the ability to analyze its environment using either predetermined rules and search algorithms or pattern-recognizing machine learning models and then make decisions based on those analyses.
93. Deep Learning: A subset of machine learning in AI that has networks capable of learning unsupervised from unstructured or unlabeled data. It’s also known as deep neural learning or deep neural network.
94. IoT (Internet of Things): A system of interrelated computing devices, mechanical and digital machines, objects, animals, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.
95. Blockchain: A distributed and decentralized ledger that records and verifies transactions across multiple computers.
96. Cybersecurity: The protection of internet-connected systems, including hardware, software, and data, from cyber threats.
97. IT Compliance: The conformance with a set of guidelines, regulations, or legislation that pertain to how an organization manages and protects its information.
98. Data Privacy: The practice of ensuring that sensitive data is kept safe from unauthorized access and theft.
99. GDPR (General Data Protection Regulation): A regulation in EU law on data protection and privacy in the European Union and the European Economic Area.
100. ITIL (Information Technology Infrastructure Library): A set of detailed practices for IT service management (ITSM) that focuses on aligning IT services with business needs.