Zachman Assessment
Enterprise architecture assessment framework to evaluate your data maturity and plan strategic improvements
15 min read
Introduction
The Zachman Framework is an enterprise architecture methodology that provides a structured way to view and define an organization. Originally developed by John Zachman in the 1980s, it has evolved into a comprehensive tool for evaluating data maturity and planning strategic improvements.
Data Governance Zachman
Enterprise data governance framework mapping business objectives to implementation
Why (Business Driven)What (Business Capabilities)How (Key Project)Where (Location)Who (People)When (Timeline)
| Why (Business Driven) | What (Business Capabilities) | How (Key Project) | Where | Who | When |
|---|---|---|---|---|---|
Contextual(Motivation) What does it matter? | |||||
Sustainable Revenue Growth (via CLV, Cross-sell) | Unified 360 Customer Data | AI Powered Customer Engagement | Digital Platforms | — | — |
Profitability Maximization (via NIM, CAC) | Profitability & Risk Data | Intelligent Risk and Profitability Management | Efficient Branch Network | — | — |
Operational Excellence & Resilience | Core Operational Data | Automated and Resilient Operations | Key Geographic Markets | — | — |
Best-in-Class Cost Efficiency (via CIR) | Legacy Data | AI Driven IT Modernization | — | — | — |
Conceptual(Business Enablement) What is the rule? | |||||
Principal: Customer centric data driven decision making | Customer Centric Data: Profile & Demographics, Product Holding, Transaction, Behaviors | Customer Management, Sales Management, Marketing Management, Product Management | Digital Banking, CRM, Partner Integration Hub | — | — |
Policy and Framework: Data Governance, Data ownership, Data life cycle management, FinOps | Value & Intelligence Data: Profitable Metric, Risk Profile, Generated Insight, Feature Sets, Process Automation Insight | Risk & Compliance Management, Credit Management, Product Management | Branch & ATM Physical Channel, Teller & RM Work Station | — | — |
Process & Procedure: Data Stewardship, Data Quality Issue Management, etc | Foundational Data: Payment and Transaction, General Ledger, Process Metadata | Payments & Transactions Management, Channel Management, Financial & Accounting Management | Logical Business Location Model | — | — |
— | — | Data Management, IT Management | Central Data Repository (Datalake, KM), Data Distribution Services | — | — |
Logical(Rules) How smart should the system be? | |||||
Data Integrity & Trustworthiness | Customer Relational Data Model | Core Customer Facing Service | Presentation Tiers: App Frontend | — | — |
Security & Access Control | Analytics & Intelligence Data Model | AI & Analytics Engines | Application & Business Logic Tier | — | — |
Lifecycle & Cost Governance | Operational & Transitional Data Models | Foundational and Operating Service | Data Tier | — | — |
Automated Workflow & Escalation Rules | — | — | Logical Data Partitioning/Tagging | — | — |
Physical(Where rule is implemented) Which tools do we use? | |||||
Business Rule Management Tool | Data lake, Data warehouse, Hybrid data lake + data house (Azure, AWS, Databricks) | S3 Iceberg, RDS, Redshift, Aurora PostGres, Glue, EMR, Airflow, Grafana | User Device, Cloud Infra | — | — |
Data Governance and FinOps Tool | Data Streaming (Kafka, Kinesis Streaming) | Kafka Consumers/Producers, Spark Streaming Jobs | Cloud Service | — | — |
Process Management Tools | Analytics Platform (Fabric, SageMaker, Databricks) | BI, Model Training, Model Service, M-View | Containerization | — | — |
— | Data Governance Platform | Metadata Scanning Engine, Data Stewardship Application, Data Lineage Engine, Catalog Search Engine & API | Database Service, Resource Tagging | — | — |
Assembly(Design Principles & Standards) How to ensure the quality? | |||||
Service Level Agreements | Detailed Design Specifications | Terraform/CloudFormation scripts, DDL scripts, Python DAG files, dbt script | Service DNS Address | — | — |
Key Performance Indicators | Source Code & Configuration Files | Java/Python source code, Dockerfile | Endpoint URL | — | — |
Operational Standards | Unit & Integration Test Cases | Power BI report file, Jupyter Notebooks, Python/FastAPI source code | Database Connection String | — | — |
Compliance and Audit Standards | Build & Deployment Scripts | YAML/JSON configuration files, Jira Automation rules, SQL queries | Object URI, IP Addresses | — | — |
Operation(Business Outcomes & KPIs) How to measure the success? | |||||
Customer Lifetime Value (CLV): increase X%
Cross-sell / Up-sell Ratio: up to X% product/customer
Customer Churn Rate: Decrease X% | Live Production Data | Live Business Operations | — | — | — |
Net Interest Margin (NIM): Increase X%
Non-Performing Loan (NPL) Ratio: Decrease 25% At RB
Fraud Loss Reduction: Decrease $XM loss | Deployed AI Services & Prediction | Executing Software Services | — | — | — |
Straight-Through Processing (STP) Rate: up to X%
System Uptime: Up to 99.95% for core services
Mean Time to Resolution (MTTR): Reduce 50% | Live Business Intelligence Dashboards | Running Data Pipelines | — | — | — |
Cost-to-Income Ratio (CIR): reduce to X%
Data Cost as % of Revenue: Reduce to X%
Time to Market for New Features: Decrease to Y% | The Live, Populated Data Catalog | Live DevOps & Release Processes | — | — | — |
Contextual
Motivation
Why (Business Driven)
Sustainable Revenue Growth (via CLV, Cross-sell)
What (Business Capabilities)
Unified 360 Customer Data
How (Key Project)
AI Powered Customer Engagement
Where
Digital Platforms
Why (Business Driven)
Profitability Maximization (via NIM, CAC)
What (Business Capabilities)
Profitability & Risk Data
How (Key Project)
Intelligent Risk and Profitability Management
Where
Efficient Branch Network
Why (Business Driven)
Operational Excellence & Resilience
What (Business Capabilities)
Core Operational Data
How (Key Project)
Automated and Resilient Operations
Where
Key Geographic Markets
Why (Business Driven)
Best-in-Class Cost Efficiency (via CIR)
What (Business Capabilities)
Legacy Data
How (Key Project)
AI Driven IT Modernization
Conceptual
Business Enablement
Why (Business Driven)
Principal: Customer centric data driven decision making
What (Business Capabilities)
Customer Centric Data: Profile & Demographics, Product Holding, Transaction, Behaviors
How (Key Project)
Customer Management, Sales Management, Marketing Management, Product Management
Where
Digital Banking, CRM, Partner Integration Hub
Why (Business Driven)
Policy and Framework: Data Governance, Data ownership, Data life cycle management, FinOps
What (Business Capabilities)
Value & Intelligence Data: Profitable Metric, Risk Profile, Generated Insight, Feature Sets, Process Automation Insight
How (Key Project)
Risk & Compliance Management, Credit Management, Product Management
Where
Branch & ATM Physical Channel, Teller & RM Work Station
Why (Business Driven)
Process & Procedure: Data Stewardship, Data Quality Issue Management, etc
What (Business Capabilities)
Foundational Data: Payment and Transaction, General Ledger, Process Metadata
How (Key Project)
Payments & Transactions Management, Channel Management, Financial & Accounting Management
Where
Logical Business Location Model
How (Key Project)
Data Management, IT Management
Where
Central Data Repository (Datalake, KM), Data Distribution Services
Logical
Rules
Why (Business Driven)
Data Integrity & Trustworthiness
What (Business Capabilities)
Customer Relational Data Model
How (Key Project)
Core Customer Facing Service
Where
Presentation Tiers: App Frontend
Why (Business Driven)
Security & Access Control
What (Business Capabilities)
Analytics & Intelligence Data Model
How (Key Project)
AI & Analytics Engines
Where
Application & Business Logic Tier
Why (Business Driven)
Lifecycle & Cost Governance
What (Business Capabilities)
Operational & Transitional Data Models
How (Key Project)
Foundational and Operating Service
Where
Data Tier
Why (Business Driven)
Automated Workflow & Escalation Rules
Where
Logical Data Partitioning/Tagging
Physical
Where rule is implemented
Why (Business Driven)
Business Rule Management Tool
What (Business Capabilities)
Data lake, Data warehouse, Hybrid data lake + data house (Azure, AWS, Databricks)
How (Key Project)
S3 Iceberg, RDS, Redshift, Aurora PostGres, Glue, EMR, Airflow, Grafana
Where
User Device, Cloud Infra
Why (Business Driven)
Data Governance and FinOps Tool
What (Business Capabilities)
Data Streaming (Kafka, Kinesis Streaming)
How (Key Project)
Kafka Consumers/Producers, Spark Streaming Jobs
Where
Cloud Service
Why (Business Driven)
Process Management Tools
What (Business Capabilities)
Analytics Platform (Fabric, SageMaker, Databricks)
How (Key Project)
BI, Model Training, Model Service, M-View
Where
Containerization
What (Business Capabilities)
Data Governance Platform
How (Key Project)
Metadata Scanning Engine, Data Stewardship Application, Data Lineage Engine, Catalog Search Engine & API
Where
Database Service, Resource Tagging
Assembly
Design Principles & Standards
Why (Business Driven)
Service Level Agreements
What (Business Capabilities)
Detailed Design Specifications
How (Key Project)
Terraform/CloudFormation scripts, DDL scripts, Python DAG files, dbt script
Where
Service DNS Address
Why (Business Driven)
Key Performance Indicators
What (Business Capabilities)
Source Code & Configuration Files
How (Key Project)
Java/Python source code, Dockerfile
Where
Endpoint URL
Why (Business Driven)
Operational Standards
What (Business Capabilities)
Unit & Integration Test Cases
How (Key Project)
Power BI report file, Jupyter Notebooks, Python/FastAPI source code
Where
Database Connection String
Why (Business Driven)
Compliance and Audit Standards
What (Business Capabilities)
Build & Deployment Scripts
How (Key Project)
YAML/JSON configuration files, Jira Automation rules, SQL queries
Where
Object URI, IP Addresses
Operation
Business Outcomes & KPIs
Why (Business Driven)
Customer Lifetime Value (CLV): increase X%
Cross-sell / Up-sell Ratio: up to X% product/customer
Customer Churn Rate: Decrease X%
What (Business Capabilities)
Live Production Data
How (Key Project)
Live Business Operations
Why (Business Driven)
Net Interest Margin (NIM): Increase X%
Non-Performing Loan (NPL) Ratio: Decrease 25% At RB
Fraud Loss Reduction: Decrease $XM loss
What (Business Capabilities)
Deployed AI Services & Prediction
How (Key Project)
Executing Software Services
Why (Business Driven)
Straight-Through Processing (STP) Rate: up to X%
System Uptime: Up to 99.95% for core services
Mean Time to Resolution (MTTR): Reduce 50%
What (Business Capabilities)
Live Business Intelligence Dashboards
How (Key Project)
Running Data Pipelines
Why (Business Driven)
Cost-to-Income Ratio (CIR): reduce to X%
Data Cost as % of Revenue: Reduce to X%
Time to Market for New Features: Decrease to Y%
What (Business Capabilities)
The Live, Populated Data Catalog
How (Key Project)
Live DevOps & Release Processes
The Zachman Matrix
The framework uses a 6x6 matrix combining perspectives and interrogatives
Perspectives (Rows)
- 1Executive/Planner— Scope & Context
- 2Business Management— Business Concepts
- 3Architect— System Logic
- 4Engineer— Technology Physics
- 5Technician— Tool Components
- 6Enterprise— Operations Instances
Interrogatives (Columns)
- 1What— Data (Inventory)
- 2How— Function (Process)
- 3Where— Network (Distribution)
- 4Who— People (Responsibility)
- 5When— Time (Timing)
- 6Why— Motivation (Ends/Means)