Channel partners can turn fragmented enterprise data into a service opportunity by helping customers connect systems, govern access, and deliver useful data through APIs, portals, and self-service tools. That creates a credible basis for assessment, implementation, and managed services—but available evidence does not establish that the approach guarantees higher margins, client retention, or recurring revenue.
What “data experience” means in practice
Data experience is the work of making organizational data useful and accessible to the people and applications that need it. It goes beyond putting data in cloud storage or building a dashboard: systems must exchange information, data must be trustworthy and governed, and users need an appropriate way to access it.
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Mark Wall, a TCS Consulting and Advisory Partner in the Business Transformation Group, describes it as “an enabler that the industry is adopting from the user experience domain to derive value from data.” In practical terms, that can mean exposing governed data through APIs, customer or supplier portals, internal analytics, or a data marketplace.
The opportunity is not simply to make more data visible. It is to make the right data available, with suitable freshness, quality, permissions, and context, to a defined audience.
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Why fragmented data creates a customer problem
A data silo is an isolated collection that cannot readily be shared across systems, teams, or business units. Silos can leave organizations with inconsistent records, delayed access, duplicated information, manual reconciliation, and analytics that cannot draw on a complete picture.
IBM Think, reporting findings from the IBM Institute for Business Value’s 2025 CDO Study, says nearly 77% of respondents agreed or strongly agreed that data silos hinder real-time analytics and data-driven decisions. In the same study, 83% believed silos undermine innovation by preventing ideas from being shared across departments. These are survey responses, not measurements of the revenue a particular integration project will produce.
The customer-facing consequences are easy to recognize. A shipping-status portal may be unable to show current delivery information if its shipping database does not connect to the web interface. Suppliers may continue exchanging procurement details by email when their systems do not share information. These examples illustrate the problem; they are not quantified case studies.
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What a channel partner can package
A partner can organize the work as a sequence from finding the friction to operating the resulting service. The scope depends on the customer’s systems, audience, risk requirements, and desired data freshness.
1. Discover data flows and failure points
Map where important data originates, how it moves, who uses it, and where people compensate for system gaps. Look for conflicting definitions, duplicated records, slow access, manual exports, and applications that cannot communicate. The result should be a prioritized map of business problems and dependencies, not a generic recommendation to “integrate everything.”
2. Design integration and modernization
Identify the appropriate combination of connectors, APIs, integration pipelines, and data products to get information from source systems to its intended users. TCS discusses API access to data in CRM contexts; Persistent describes integration and connector capabilities. Those provider descriptions show possible technical approaches, not a neutral guarantee that a particular product will fit every environment.
3. Establish governance and security
Define data ownership, quality expectations, access rights, and controls before opening new routes to data. Role-based access can limit what users or applications see according to their responsibilities. Auditability matters too: the organization should be able to understand who requested access and what information was made available. Integration should not turn into universal access.
4. Deliver an interface people can use
Depending on the need, the delivery surface may be a customer or supplier portal, an internal self-service marketplace, an analytics view, or an API consumed by another application. Snowflake describes data sharing and customer-facing applications; Huwise describes internal and B2B data marketplaces, including granular partner permissions and traceable access requests. These are vendor descriptions of capabilities, not independent evaluations.
5. Operate and improve the service
After launch, a partner may offer monitoring for integration failures, data quality, access, governance, and platform operations. This can be packaged as ongoing support if the customer values and funds it. It is a possible service model, not proof of guaranteed recurring revenue.
How to evaluate an implementation approach
Do not choose a portal or marketplace before understanding the systems and rules behind it. Compare approaches against the customer’s actual use case:
- Integration breadth: Can it work with the customer’s legacy and cloud systems, and what custom work is required?
- Freshness and latency: Does the use case need near-real-time updates, scheduled refreshes, or only periodic reporting?
- Quality and governance: How will definitions, ownership, validation, and correction be handled?
- Permissions and auditability: Can access be scoped to roles, partners, or specific data, and can activity be traced?
- Audience and delivery: Is data for internal teams, business partners, customers, or an application interface?
- Deployment and region: Do deployment choices and regional requirements fit the organization’s operating constraints?
- Usability and adoption: Can intended users find and understand the data without creating new manual work?
- Total cost: Account for implementation, integration maintenance, governance, and ongoing platform operations.
A marketplace or portal can improve discovery and access, but it cannot by itself repair unreliable source data, settle ownership questions, or create suitable permissions. Those foundational issues belong in the project scope.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsData monetization is not the same as partner revenue
Organizations may monetize data by selling datasets, offering derived insights or applications, or sharing data with business partners. That is an enterprise business model. A channel partner’s potential revenue instead comes from services it sells to help a customer design, implement, secure, or operate the underlying capability.
Best Value
Cloud spending is relevant context, not proof of demand for data-experience projects. Omdia reported global cloud infrastructure services spending of US$110.9 billion in Q4 2025, up 29% year over year, and forecast 27% growth for 2026. Those figures describe cloud infrastructure spending and its forecast; they do not measure a data-experience market or establish partner margins.
What the revenue case can—and cannot—claim
The case for a partner offer is that organizations can invest in cloud infrastructure and still struggle to make their data usable. Discovery, integration, governance, implementation, and operations give a partner concrete work to scope and deliver. A partner can test whether customers will pay for that work by tying proposals to specific outcomes such as reducing manual data handling or enabling a defined portal use case.
The cited evidence does not demonstrate that adopting a data-experience strategy by itself increases channel margins, retention, or recurring revenue. Treat those results as hypotheses to validate against each customer’s budget, measurable operational problem, and willingness to maintain the service—not as established market outcomes.
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