Technology Business Data Model: AI-Ready Edition

The Technology Business Data Model: AI-Ready Edition is for CIOs, architects and transformation leads who need to know what information technology work runs on before an AI agent touches it. It covers 18 subject areas, 125 entities, 842 key attributes and 428 relationships. Every entity and key attribute is classified for sensitivity, with the AI uses and data-quality requirements an agent depends on. It is the data-model part of Business Architecture for Technology: AI Transformation Blueprint, sold on its own.

What's Inside

The same model comes in three files: the full model in Word, a workbook to filter and extend, and a guide to the scales and the license.

• 18 subject areas and 125 entities, each with a definition, its typical system of record, sensitivity class, AI uses and data-quality requirements
• 842 key attributes with sensitivity and AI relevance, and 428 relationships with cardinality
• Under each entity, the capabilities that need it and the agents that read it, by name and ID
• The Business Data Model (Word): every subject area and entity in full
• The workbook (Excel): subject areas, entities, attributes and relationships in sheets you can filter and extend
• The guide (Word): the scales the model refers to, the data foundation, and the license
• Free corrections, and new versions free for 180 days

Every file names your organization and carries your license ID.

The 18 Subject Areas

The 125 entities are grouped into 18 subject areas. The list gives what each holds and how many entities it has.

• Technology Strategy, Governance & Organization (7 entities): How the technology function is directed and organized: the business areas it serves, the technology strategy and roadmap, its governance forums and decision rights, its teams and the skills they hold.
• Demand, Investment & Portfolio (7 entities): What the technology function chooses to do: demand from business areas, investment cases and decisions, the portfolio, projects, the benefits they promise and technology trials.
• Architecture, Applications & Integration (9 entities): The shape of the technology estate: the business capabilities it supports, architecture reviews and deviations, approved technology standards, solution designs, applications and their assessments, and the interfaces and interface contracts between them.
• Requirements & Software Engineering (6 entities): How software is built: requirements, code repositories, code changes, code review records, engineering standards and pipeline runs.
• Testing & Release (6 entities): How software is proven and released: test plans and results, defects, test data sets built without personal data, releases and release readiness assessments.
• Environments & Infrastructure (8 entities): The infrastructure services run on: environments, infrastructure definitions, servers, storage, network devices, database instances, platform services and digital certificates.
• Cloud, Data Center & Edge (7 entities): Where workloads are hosted: cloud accounts and resources, cloud commitments, migration waves, data center facilities, edge sites and the connected devices they serve.
• Observability, Capacity & Operations (7 entities): How running services are watched and kept within capacity: alerts, correlated events, batch jobs, runbooks and their execution records, capacity forecasts and availability targets.
• Patching, Backup & Disaster Recovery (8 entities): How systems are kept current and recoverable: patches and their deployments, maintenance windows, backup policies and jobs, restore tests, disaster recovery plans and disaster recovery tests.
• Services & Service Levels (5 entities): What the technology function offers and promises: technology services, service catalog entries, service level agreements, service level results and service improvement items.
• Support, Incidents & Problems (7 entities): How users are supported when something goes wrong: support contacts, incidents, major incident records, incident communications, problems, known errors and knowledge articles.
• Requests & Changes (8 entities): How users ask for things and how production changes: request types, service requests, joiner, mover and leaver requests, standard change models, change requests, change risk assessments, change authorizations and post-implementation reviews.
• Configuration & Hardware Assets (6 entities): What the estate is made of and how it fits together: configuration items, configuration relationships, configuration baselines, hardware assets, asset assignments and asset disposal records.
• Workplace & End-User Technology (6 entities): The technology employees use every day: technology users, end-user devices, device enrollments, software deployments, experience measure results and assistive technology requests.
• Technology Finance (6 entities): What technology costs and who pays: technology budgets, spending forecasts, spending records, spending approval limits, service costs and cost allocation rules, reconciled with the finance function every period.
• Vendors, Contracts & Licenses (8 entities): Who the technology function buys from and on what terms: technology vendors, contracts, contract obligations, vendor performance reviews, vendor risk assessments, software entitlements, license positions and contingent engagements.
• Policy, Risk & Compliance (7 entities): How technology risk is governed: technology policies and their exceptions, technology risks, safeguard test results, compliance evidence items, audit findings and security remediation tasks.
• AI & Digital Labor Governance (7 entities): How AI and AI agents in the technology function are governed: AI systems, AI agents, agent action logs, AI decision records, model validation records, human review records and agent authority limits.

Who Uses It

Data owners and stewards, data architects, and AI and analytics engineers who need to know what an agent may read, how sensitive it is and how good it must be first; and business architects who link capabilities to data.

How It Fits With the Other Products

The capabilities named under each entity are defined in the Technology Capability Model: AI-Ready Edition. The agents are specified in Business Architecture for Technology: AI Transformation Blueprint, which contains this data model and adds the value streams, use cases, controls, an operating model and a roadmap. The Technology Value Streams are sold on their own too.