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SGKG is proudly supported by Team400, an Australian AI consultancy helping enterprises navigate practical AI implementation.
Knowledge governance and data standards
Best practices for managing knowledge assets at scale.
Clear, practical guidance for data professionals and governance practitioners. We focus on standards, frameworks, and proven approaches that work.
What we cover
- Data governance frameworks and standards
- Knowledge management systems
- Metadata and information architecture
- Compliance and policy implementation
What you can expect
- Clear explanations of complex standards
- Implementation guidance and templates
- Case examples from real programs
- Best practices from industry leaders
Latest posts
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Data Lineage Tools Compared: What's Actually Working Mid-2026
An honest comparison of data lineage tools in 2026 — what each does well, where the integration challenges remain, and what data governance teams should choose.
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AI Governance for Analytics Teams: What Actually Works in 2026
AI governance frameworks designed for executive presentation often fail at the analytics team level. Here's what actually works for the teams doing the day-to-day work.
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Are AI-Generated Knowledge Graphs Replacing Traditional Enterprise Taxonomies?
Vendors are pitching LLM-generated knowledge structures as a replacement for hand-curated taxonomies. The evidence so far suggests a more nuanced answer.
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Data Stewardship Roles in 2026: What's Working and What's Quietly Failed
After a decade of data stewardship programs, the patterns that produce real accountability versus organisational theatre are starting to become clear.
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Data Product Discipline in Mid-2026: What's Actually Working
Data-as-a-product practices have matured into operational discipline at organisations that committed early. A look at what's working and what's still being figured out.
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Metadata Management Tools in 2026: A Practitioner's Assessment
The metadata management tools market in 2026 — what's mature, what's still developing, and what to actually buy if you're building data governance now.
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Data Taxonomy Design — Practical Principles for May 2026
Practical principles for designing data taxonomies and information classification schemes that actually get adopted and maintained.
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Knowledge Graph Implementation in Enterprises — A Working Read for May 2026
A practical look at where enterprise knowledge graph implementation sits in May 2026 — the use cases, the tooling, and the realistic delivery patterns.
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Data Catalog Adoption Patterns in Mid-2026 — A Working Read
A working read on how enterprise data catalog tools have actually been adopted through 2024-25 and where the practice sits in May 2026.
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Data Mesh Revisited in Mid-2026 — What's Actually Working
A working read on data mesh adoption through 2024-25 and what the operating model has actually produced in May 2026.
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Lakehouse Table Formats in May 2026 — Where They Have Landed
Iceberg, Delta Lake, and Hudi have spent five years in a race for the lakehouse standard. The May 2026 read on where the market has settled.
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Data Contracts in Production — A May 2026 Practitioner Read
Data contracts have moved past the theory phase. Here is the May 2026 read on what is working in production and where the practice is still maturing.
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Data Mesh vs Data Fabric in 2026: The Decision Most Organisations Should Have Already Made
The data mesh vs data fabric question has matured. A practical framework for which approach fits which organisation in 2026.
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Metadata Management Tooling in 2026: The Vendor Landscape and the Buying Decision
Metadata management has moved from an underinvested area to a strategic data capability. The 2026 vendor landscape and what to look for.
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Metadata Quality Metrics That Drive Behaviour, Not Just Reports
Most metadata quality dashboards are read once and ignored. The metrics that actually change behaviour are narrower and harder to negotiate.