Own the product vision
Set vision, roadmap, and priorities for analytics and AI-enabled data products.
Architecture Path · Products & Consumption · Step 7A
Data Products & Analytics Marketplace
The program for the leader who owns enterprise analytics, AI-enabled data products, governed self-service, and the enterprise data marketplace. Build the product vision, the semantic and ontology layer, the marketplace and catalog, and the adoption and value measurement that turn trusted data into consumed insight, mapped to the Director of Data Products and Analytics role.
8
Modules
40
Chapters
Director
Level
Capstone
Marketplace + product strategy
The journey
Eight modules, one arc
The eight modules build cumulatively toward a real capstone. Watch the work move, and the value compound, at every stage.
Each module builds the capability the next one depends on, ending in a portfolio-ready capstone.
Outcomes
What you'll be able to do
Build a semantic layer
Design ontology-driven semantic models, business-friendly metrics, and knowledge-graph context.
Stand up a marketplace
Define cataloging, metadata, discoverability, access patterns, and usage transparency.
Enable governed self-service
Make trusted data discoverable, secure, and easy to consume for the business.
Bring AI to analytics
Use natural-language analytics, intelligent search, and GenAI to improve discovery and insight.
Measure value
Define metrics for adoption, reuse, trust, satisfaction, and realized business value.
Curriculum
8 modules, 40 chapters, ending in a capstone
Eight modules of five chapters each, sequenced so the material builds cumulatively to a real, portfolio-ready capstone. Expand any module for its focus and lessons.
01 The Data Product Operating Model
Treat analytics and data as products with owners, users, and value.
- From projects and reports to data products
- The product vision, roadmap, and prioritization
- Users, consumption patterns, and decision needs
- Reusable data products versus one-off deliverables
- The operating model that owns and evolves products
02 Requirements and Value Discovery
Translate business decision needs into actionable product requirements.
- Partnering with business stakeholders on decisions and pain points
- Profiling data and clarifying grain, keys, and relationships
- Turning needs into use cases, user stories, and data requirements
- Defining acceptance criteria, controls, and dependencies
- Sequencing requirements into a delivery-ready backlog
03 Semantic Layers, Ontology and Knowledge Graphs
Build the business-friendly meaning layer analytics and AI consume.
- Semantic layers: business-friendly metrics and definitions
- Ontology-driven models that capture business concepts
- Knowledge graphs: connecting data, relationships, and context
- Canonical metrics and a single source of definition
- Designing a semantic model for a business domain
04 The Data Marketplace and Catalog
Design the marketplace that makes trusted data discoverable and consumable.
- Data marketplace strategy and its building blocks
- Cataloging, metadata, and business glossaries
- Discoverability, addressability, and product onboarding
- Certification and trust signals for data products
- Designing the marketplace experience end to end
05 Governed Access and Consumption
Make self-service access trusted, secure, and controlled.
- Access request patterns and governed self-service
- Least-privilege access and sensitive-data controls
- Usage transparency and consumption monitoring
- Aligning access to enterprise policy and standards
- Designing a governed access model for the marketplace
06 AI-Enabled Analytics
Use AI to improve discovery, insight, and the consumption experience.
- Natural-language analytics and intelligent search
- GenAI for insight generation, summarization, and documentation
- AI-assisted data discovery and requirements development
- Anomaly detection and predictive analytics in products
- Designing an AI-enabled analytics capability responsibly
07 Analytics Tooling and Platform Roadmap
Shape the tooling and platform so insight is easy to consume.
- The analytics tooling landscape: BI, self-service, and notebooks
- KPI frameworks, metrics layers, and governed reporting
- Enterprise data platforms and patterns that feed products
- Building a capability roadmap for tools and experiences
- Maturing analytics operating practices toward self-service
08 Capstone: A Data Marketplace and Product StrategyCapstone
Assemble a marketplace and product strategy with adoption and value metrics.
- Define the product portfolio and marketplace vision
- Specify the semantic layer and a flagship data product
- Design the catalog, access model, and AI-enabled experience
- Define success metrics: adoption, reuse, trust, and value
- Capstone: present a marketplace and data-product strategy as a portfolio artifact
Who it's for
Built for Directors owning data products, self-service analytics, and the data marketplace
Directors of data products
Leaders owning data products, BI, and self-service analytics capability.
Analytics and BI leaders
Heads of analytics modernizing toward governed self-service.
Data marketplace and catalog owners
Those shaping a data marketplace, catalog, or consumption strategy.
Senior data professionals
20+ year practitioners moving from delivery into product leadership.
Program formats
How you learn
Self-paced
Work through it at your own pace, with lifetime access to every module and the capstone.
Mentor-led cohort
A guided cohort with live sessions, reviews, and a peer group working the same path.
Private corporate
A closed cohort for your team, tailored to your platforms, domains, and priorities.
Portfolio-building
Every module produces an artifact; the capstone assembles them into a portfolio deliverable.
For teams
Bring it to your team
Run Data Products & Analytics Marketplace as a private, closed cohort tailored to your platforms, domains, and priorities, as part of building the architecture capability your organization needs.
Domain & leadership
From the corporate programs
FAQ
Data Products & Analytics Marketplace - answered
Which role does this map to?
The Director or Head of Data Products and Analytics Marketplace: owning enterprise analytics, AI-enabled data products, governed self-service, and the enterprise data marketplace, typically in wealth, brokerage, advisory, or asset-management financial services.
What makes it different from a BI program?
It is a product-and-marketplace leadership program. It covers semantic layers and ontology, knowledge graphs, the marketplace and catalog, governed access, AI-enabled analytics, and value measurement, not just building dashboards.
Does it cover semantic layers and ontology?
Yes, in depth: ontology-driven semantic models, business-friendly metrics and definitions, and knowledge-graph concepts that connect data, relationships, and business context for analytics and AI.
Is AI covered?
Yes. A full module covers natural-language analytics, intelligent search, GenAI for insight and documentation, and AI-assisted discovery, applied to trusted enterprise data.
What is the capstone?
A data marketplace and data-product strategy: portfolio vision, semantic layer, a flagship product, the catalog and access model, an AI-enabled experience, and adoption and value metrics, as a portfolio artifact.
Who is it for?
Directors of data products, analytics and BI leaders, marketplace and catalog owners, and senior practitioners moving from delivery into product leadership.
Take the next step on the path
Enrol, enquire, or explore the full IC-to-Head of Data Architecture path.