Data & Infrastructure
The fuel that powers AI success
The Data & Infrastructure pillar assesses the quality, accessibility, and governance of your data, as well as the technical infrastructure supporting AI systems. Good data is the fuel that powers effective AI.
Assessment Areas
Data Quality
Accuracy, completeness, and consistency
L0: Poor qualityL1: InconsistentL2: Cleanup underwayL3: Good in key areasL4: Enterprise-wide quality
Data Accessibility
Ease of access for AI systems
L0: Siloed dataL1: Manual exportsL2: Basic APIsL3: Integrated platformL4: Real-time streaming
Security & Compliance
Protection and regulatory adherence
L0: No policiesL1: Basic securityL2: Compliance effortsL3: Strong governanceL4: Industry-leading
Infrastructure Scalability
Capacity for AI workloads
L0: Legacy systemsL1: Basic cloudL2: Cloud AI capabilitiesL3: Scalable platformL4: Enterprise AI platform
Best Practices
- Invest in data quality before AI implementation
- Create unified data platforms for AI accessibility
- Implement data governance from the start
- Plan for scalability of AI workloads
- Establish clear data ownership and stewardship
- Regular data audits and quality checks
Common Mistakes
- Underestimating data quality requirements
- Keeping data siloed across departments
- Ignoring security and compliance needs
- Not planning for infrastructure scaling
- Lack of data governance and ownership
Sample Assessment Questions
1What is the quality and accessibility of your data for AI?
2Do you have APIs and data pipelines to feed AI systems?
3Is your infrastructure scalable for AI workloads?
4How do you ensure data security and compliance?
5Is there clear data ownership and governance?
Assess Your Data & Infrastructure
Take our comprehensive assessment to get detailed scores and recommendations for this pillar and all others.