Metadata Management & Data Catalog Strategy.
Make your organization’s data assets findable, understandable, and trustworthy — with a metadata management program and data catalog strategy built on the information architecture disciplines that make AI, search, and governance actually work.
Data Management Services
The Situation — When Clients Come to Us
Organizations come to us for metadata management when:
- Data assets exist across the organization but can’t be found, understood, or trusted — because metadata is absent, inconsistent, or undocumented
- A data catalog has been purchased and deployed but adoption is low because the underlying metadata schema was never properly designed, the taxonomy was never defined, and nobody owns the stewardship
- AI, GenAI, or enterprise search programs are underperforming because the content and data they reason over lacks the semantic structure, classification, and metadata quality those systems require
- Data governance and compliance programs require documented data lineage, data provenance, and an authoritative business glossary that the organization currently cannot produce
- The organization is preparing a data catalog implementation and needs metadata strategy, schema design, and taxonomy work done before — not after — the tool is configured
What We Do — Our Approach
// Phase 1
Metadata Inventory & Gap Analysis
We conduct a comprehensive audit of existing metadata across the organization’s data estate — assessing technical metadata (schemas, data types, lineage), business metadata (definitions, ownership, usage), and operational metadata (quality, update frequency, access controls). We identify gaps, inconsistencies, and the highest-value metadata to prioritize.
// Phase 2
Metadata Strategy & Architecture Design
We develop the metadata strategy — defining the metadata framework, scope, stewardship model, and the integration approach between metadata management and the organization’s governance, data quality, and AI programs. We design the enterprise metadata schema and business glossary structure.
// Phase 3
Taxonomy & Controlled Vocabulary Design
We design the taxonomies, controlled vocabularies, and classification structures that organize data assets for discovery, governance, and AI use — drawing on Iknow’s deep information architecture expertise to build metadata vocabularies that are precise, maintainable, and aligned to how users actually search and navigate.
// Phase 4
Data Lineage Design
We design the data lineage framework — mapping the flow of critical data assets from source through transformation to consumption — providing the traceability required for regulatory compliance, AI explainability, and governance accountability.
// Phase 5
Data Catalog Platform Advisory & Stewardship Design
We provide vendor-neutral evaluation of data catalog platforms (Collibra, Informatica, Alation, Microsoft Purview, and others) against the metadata architecture and organizational requirements. We design the stewardship model — roles, workflows, and quality monitoring — that keeps the catalog accurate after implementation. Platform configuration is performed by the client or technology partner.
What You Get — Deliverables
- Metadata inventory and gap analysis report
- Enterprise metadata strategy and architecture design
- Enterprise metadata schema and business glossary structure
- Taxonomy and controlled vocabulary design for data asset classification
- Data lineage framework design and critical data flow maps
- Data catalog platform evaluation with vendor-neutral selection recommendation
- Metadata stewardship model — roles, workflows, and quality monitoring specifications
- Implementation guidance package for the client or technology partner
- Metadata quality baseline and improvement tracking framework
Your data catalog is only as good as the metadata strategy behind it.
Iknow brings the information architecture expertise — taxonomy design, metadata schema, controlled vocabulary, data lineage — that most data management firms cannot provide.