What is a data product?
A data product is a self-contained, governed asset that packages trusted, fit-for-purpose data to answer a specific business question or power a decision — with a clear owner, SLAs, documented semantics, lineage and policy, all behind a published interface.
In short: not a table. Not a dashboard. A product — built, owned, versioned and consumed.
The mindset behind it is data as a product.
Raw data vs. data products
The value isn't in the ingredients alone — it's in turning trusted ingredients into a packaged product that people can safely and confidently consume.
Like cocoa, sugar, milk, cocoa butter, lecithin and vanilla on a supermarket shelf. Useful in isolation — but the customer has to know what each ingredient is, how they relate, whether they're good quality, and how to combine them correctly. The burden falls entirely on the consumer.
Like a finished, branded chocolate bar. Packaged for purpose, quality assured, versioned, labeled and governed — with clear ownership, usage guidance, business definitions and full lineage back to the source ingredients. Ready to consume with confidence.
From raw beans to a trusted bar
Raw ingredients are useful on their own, but a trusted product is packaged, governed, labeled, versioned, owned and ready to consume. Data is the same.
Cacao beans on the farm. Sugar cane in the field. Milk in the dairy. Vanilla beans on the vine. Cocoa butter and lecithin extracted from their own sources. All raw, all in different places.
CRM, ERP, billing, IoT, spreadsheets, third-party feeds. All raw, all siloed, each owned by a different team in a different system.
Beans fermented, roasted and refined. Milk is pasteurised and vanilla prepared. Each ingredient becomes usable, but they still exist separately.
Each source is cleaned, modeled and quality checked. Useful on its own, but not yet combined into a trusted business asset.
Cocoa, sugar, milk, cocoa butter, lecithin and vanilla — combined in the right ratios, batch-tested, labeled, branded. A bar people trust.
Multiple processed sources fused, governed, owned, versioned and published as a data product — ready to drive a decision.
The real picture only emerges when every ingredient travels its own path and then combines under governance — that's where raw data finally becomes a trusted data product.
The ingredients of a trusted data product
Raw source ingredients — each from a different place, unprocessed, unvalidated and without context until combined.
Data quality checks and validation rules applied at source.
Lineage and metadata — where the data came from and how it was transformed.
Data product ownership and trust — a named, accountable team behind the product.
Business-friendly interface, documentation, and discoverable contracts.
Freshness guarantees and SLA commitments for data consumers.
Versioning — so consumers know exactly which release they're using.
Business definitions and usage context — what this data means and how to use it.
Access controls, sensitivity classifications, and compliance rules.
A governed data product is the finished chocolate bar. A fused or AI-ready data product is the chocolate dessert — combining multiple bars and ingredients into something even more powerful, built on a foundation of trusted, reusable components.
From "where is the data?" to "what decision does this serve?"
Traditional data work starts with sources. Data products start with the business outcome and work back. The market is moving from data-driven to decision-driven — and that is exactly where Latttice operates.
"Give me everything you have on customers." Ship the warehouse and hope the right answer falls out.
"I need to decide which customers to retain this quarter." A data product packages exactly that — trusted, governed, ready to use.
What makes data a product
Industry consensus converges on eight attributes. Miss any one and it's a dataset, not a product.
Has a stable, unique address so any system, person or agent can reliably find and call it.
Available through governed interfaces — APIs, SQL, files — with the right permissions, not buried in a warehouse.
Tied to a real business outcome. If no one would pay for it, it isn't a product.
Published in a marketplace so consumers can find it, understand it and request access.
Documented in business language — definitions, owners, freshness, examples — not raw column names.
Access, masking and audit are policy-as-code, enforced at runtime, not bolted on after.
Standard formats, contracts and identifiers so products compose cleanly across domains.
Quality, lineage and SLAs are observable and certified — consumers can see the trust score.
Foundational. Fused. Analytical.
Most enterprise portfolios mix all three — composed and re-used, not rebuilt for every project.
Canonical entities the whole enterprise depends on — Customer, Asset, Employee, Product, Location.
Multiple sources combined into a governed domain view — e.g. a 360° Customer or an Operations product.
Metrics, scores, features and model outputs that directly inform a decision or action.
Latttice, the Data Product Workbench
Latttice is the workbench teams use to design, build, govern and publish data products — and the marketplace where the business, applications and AI consume them. The 8 tenets aren't a checklist you bolt on at the end; they're how every product is built from day one.
Compose products from sources with AI-assisted modeling and contracts.
Policy-as-code, lineage and trust scoring enforced at runtime.
Versioned, addressable products with SLAs, owners and discoverable metadata.
A governed marketplace for people, applications and AI — one source of truth.
The shift is from data-driven to decision-driven — and that's exactly where Latttice operates.
The Data Product Journey
Six stages most organizations move through on the way from raw data to trusted, AI-ready decision-making.
Organizations have more data than ever before.
Business teams struggle to find, understand, and trust data.
Governance becomes increasingly difficult as environments grow.
Reusable, governed, business-focused assets emerge.
Trusted data products support better business decisions.
AI agents and copilots consume trusted data products safely.
Wherever your organization sits on this journey, the next module shows what to learn — and the knowledge check shows where you stand today.
Build your understanding, one module at a time
Six short modules — each three to four minutes — covering the concepts every executive needs to confidently lead a data product program. Open any card to explore.
Continue your executive learning journey — additional learning paths are being developed for Data Product Practitioner, Active Governance Foundations, AI Readiness Foundations, Latttice Practitioner Certification, and Lenz AI Agent Foundations.
Ready to test what you've learned? Continue to the knowledge check below. Start the Knowledge Check
Test what you've learned — and learn as you go
Twelve short questions across data products, ownership, governance, trust, AI readiness, and business enablement. Each answer reveals why it matters and how Latttice helps — this is a learning experience, not a test.
Which best describes a data product?
See data products in your environment
A short executive assessment to see where your business stands — and what the most useful next step looks like for your organization.
Where is your business on the path from business-blocked to decision-ready & AI-ready?
Trusted data drives decisions — and AI can't be achieved without it. Ten quick, thought-provoking questions to see where your organization stands today.
Data execs are using this assessment to start honest internal conversations — about why years of data transformation spend still hasn't brought data closer to the business, and what it will take to change that before the next wave of AI investment.
Privacy and Data Use Notice: This assessment does not ask for or collect personal information. Data Tiles may collect anonymous response data points to better understand industry needs, share aggregated insights with our community, and guide the future direction of our products. We listen to what the industry needs and aim to build tools that address those needs.
- 1
Does your business currently treat data as a product — packaged, reusable, governed assets the business relies on?
Not dashboards or pipelines built one-off. Reusable products with an owner, an SLA, and known consumers.
- 2
Who builds the data products your business uses?
Who actually owns and ships them — not who consumes them.
No sign-up. No personal details. Just 8 more quick questions to see where your organization stands.
Your Personalized Data Product Roadmap
Based on where your organization sits today, here is what to learn next, the module to focus on, and the single action that moves you forward. Find your level below.
You see the value of data, but trust, ownership, and reuse still live in different places across the organization.
Governance is on the agenda, but it lives alongside the data rather than inside it — and accountability for outcomes is unclear.
Early Data Products exist in pockets of the business — the opportunity now is repeatable, governed creation across domains.
Trusted Data Products are showing up at the point of decision — the next horizon is AI readiness and agent enablement.
Not sure which level fits? Complete the Data Product Readiness Assessment above, then choose the next step that best matches your organization.
Continue Your Learning Journey
A short list of next steps based on where you are today. Learn more, share internally, watch Latttice in action, or discuss your results with our team.
An eight-page PDF for executives — definition, the shift to data products, and a printable worksheet.
Download PDFHow data products are reshaping decision-making across regulated, data-intensive industries.
See industriesSee the data product workbench operate end-to-end — from connection to active consumption.
Watch the tourContinue Your AI Readiness Journey
Trusted Data Products are the foundation for AI readiness. Explore how governed, reusable Data Products help organizations prepare for copilots, AI assistants, and future agent-based workflows.
See Latttice with your own use case.
Bring us a business challenge, decision or data product idea. We'll show how Latttice can bring it to life using realistic synthetic data, without requiring access to your private data.
No sales pitch. Just a tailored demonstration for your scenario.
Start a Data Conversation
See what becomes possible when your data is finally accessible.
If your business could access trusted data instantly, what decisions would move faster?
Latttice puts data products directly into the hands of the people who use them.
Want to talk through your data product challenge?
Share where you are, what's blocking progress, and how trusted data products could help — we'll connect you with the right person on the Latttice team.