Data Tiles Says AI Is Changing How Business Teams Need to Access Trusted Data

Following the Antwerp Summit, CEO Cameron Price argues for keeping technical complexity under the hood while enabling business teams to build with governed data

As AI changes how organizations make and automate decisions, Data Tiles Founder & CEO Cameron Price says the starting point for creating data products needs to change.

Speaking at the 3rd Industry Summit on Data Product-Oriented Architectures at Antwerp Management School, Belgium, Price argued in his presentation, “Stop Building Data Products in the Data Team,” that traditional approaches have built a supply chain around data, from source systems, through data teams and data products, into reports and eventually to the person making the decision.

The data team needs confidence that everything under the hood is working. The business team needs to be able to turn the key and get on the road.”

— Cameron Price, Founder & CEO, Data Tiles

“The decision became the last mile.”

Price advocates flipping that model: “Start with the decision. Work backwards to the data.”

One decision. Too many places to look.

In Antwerp, Price illustrated the problem through Sarah, a claims assessor deciding whether a claim should be investigated. Her evidence is spread across multiple systems, documents and people.

Sarah does not need another dataset. She needs trusted context to answer the business questions that matter.

Rather than beginning with a dataset, schema or technical model, Price advocates asking: What decision needs to be made? What context is required? What evidence supports it? What outcome is expected?

Then work backwards to the data.

Put the complexity under the hood

This does not mean removing the technical foundations required to create trusted data products.

Technical metadata, relationships, semantic meaning, security, access controls, lineage, policy enforcement, auditability and lifecycle governance still need to be there. Data and governance teams remain essential to establishing trusted source access, reusable foundations, policies, standards and controls.

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The difference is who needs to experience that complexity.

For data teams, those foundations and controls provide confidence that what is happening underneath is trusted, governed and explainable. For business teams, that complexity can remain behind the scenes, allowing people to work in the language of their business, their context and the decision they need to make.

Price compares it to driving a car:

“The data team needs confidence that everything under the hood is working. The business team needs to be able to turn the key and get on the road.”

Data Tiles applies this principle through Latttice, its zero-code, AI-powered Data Product Workbench. Latttice brings technical and business metadata together to create semantic understanding while maintaining the relationships, security, access controls and governance required for trusted enterprise data.

Complexity is abstracted away. Control is not.

AI makes the distance matter more

People can compensate for fragmented information by searching reports, moving between systems, asking colleagues or waiting for specialist teams. AI assistants and agents cannot spend days finding and interpreting the right information.

Trusted context, business meaning and governance need to be available when a question is asked or an action is taken.

“AI is forcing organizations to confront how far their data still sits from the decisions it is supposed to support,” Price said. “Whether the consumer is a person or a machine, the objective is the same: bring trusted data to the point of decision.”

A decision-driven data product is not created for a single interface or output. Once the context, meaning and governance required for a decision have been brought together, the same governed data product can be reused wherever it is needed. It can support a business user, BI, an application or workflow, an AI assistant or an agent.

Organizations do not need to recreate trusted business context each time the way data is consumed changes. Create the governed data product once and make it available wherever decisions happen.

Create Once. Govern Once. Use Everywhere.

Price summarized the opportunity simply: “Business knows the decision. Data knows the evidence. Bring them together and build backwards from the decision.”

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