Welcome to the Data, AI & Platform Team Knowledge Base.
This wiki is the single source of truth for all technical documentation, standards, and operational knowledge managed by the Data, AI & Platform Teams.
This space is designed to support:
- Daily operations
- Architecture understanding
- Standardized processes
- Security & compliance requirements
- Continuous improvement across the platform
This documentation hub exists to:
- 📘 Centralize all IT knowledge related to Data, AI, and Platform
- 🧩 Provide clear architecture and system design references
- 🔁 Standardize SOPs, runbooks, and operational procedures
- 🔐 Support security, audit, and compliance (e.g. ISO 27001)
- 🚀 Enable faster onboarding, troubleshooting, and delivery
This wiki covers the following domains:
- Server & VM architecture
- Container & orchestration platforms
- Storage, networking, and virtualization
- Monitoring, logging, and backup strategies
- Data Lakehouse architecture
- ETL / ELT pipelines
- Data warehouse & BI
- Data governance & metadata
- AI platform architecture
- Model lifecycle & deployment
- RAG / LLM integration
- AI use cases & experimentation guidelines
- Security architecture & controls
- ISO 27001 documentation
- Risk registers & mitigation plans
- Access control & segregation of duties (SoD)
- Incident response procedures
- Troubleshooting guides
- Backup & disaster recovery
- Maintenance & change management
- Current state architecture
- Target / future architecture
- Architecture Decision Records (ADR)
- Design standards & best practices
This documentation is intended for:
- Data Engineers
- Platform / DevOps Engineers
- AI Engineers & Analysts
- IT Operations
- Security & Compliance teams
- Internal auditors and stakeholders (read-only)
- 🔍 Search first – most common questions are already documented
- 📂 Follow the navigation structure for your domain
- 📑 Use runbooks during incidents and operational tasks
- 📝 Keep documentation up to date after changes or improvements
- 📌 Reference this wiki during design reviews, audits, and onboarding
To maintain quality and consistency:
- Follow the defined documentation templates
- Keep content clear, structured, and actionable
- Update documents after system or process changes
- Do not store sensitive credentials or secrets
- Respect access roles and approval workflows
If you are unsure where to place documentation, consult the Architecture or Platform section or contact the team owner.
¶ 🔄 Ownership & Maintenance
This wiki is maintained by the Data, AI & Platform Teams.
- Platform Owner: Data, AI & Platform
- Review Cycle: Periodic / As-needed
- Source of Truth: This Wiki
New to the platform? Start here:
- Architecture Overview
- Platform & Infrastructure
- Data Platform Basics
- Operations & Runbook
- Security & Compliance