Creating a Data Sharing Business Model Opportunities and Benefits

Creating a Data Sharing Business Model: Opportunities and Benefits


Table Of Contents

Simplifying data sharing throughout an organization demands the development of an effective data sharing business model. This model outlines the technicalities of data movement inside and outside of the business, and also ensures privacy and security are maintained.

Creating an effective data sharing business model for your organization requires:

  • From a technical mindset, a strategic approach involving establishing a data sharing framework, trust networks, and of course, data governance
  • From a non-technical perspective, demonstrating the “why” behind data sharing and getting buy-in from stakeholders is a must.

Let’s start with data sharing in the cloud and how it helps remove some of the barriers that prevent some businesses from taking full advantage of data sharing initiatives.

Why are Businesses Using Cloud for Data Sharing

The digital cloud has changed the scope of what is possible with sharing data. The cloud is not only the most cost-effective solution for providing on-demand information access with nearly unlimited storage capabilities, but it also prioritizes security, which makes it the perfect solution for effective data sharing.

1. Cost-Effectiveness

Data sharing in the cloud is currently the most cost-effective way to store and share data. Cloud-sharing programs like AWS and Microsoft Azure allow organizations to share petabytes of data without the high costs.  In addition, when data is shared using Revelate, data is not stored on Revelate’s system. Instead, data is extracted from the source via an on-demand basis. In other words, when the customer requests a data set listed on your Revelate data web store, the process of extracting, processing, preparing, and distributing that dataset to the customer is handled automatically at that time, rather than having listed datasets stored on Revelate’s servers.

2. Democratizes Data Access

Through the cloud, organizations are able to share data in a fully-governed and secure environment internally and externally, eliminating departmental data silos and reducing pressure on IT teams to manually fulfill data orders. In other words, a cloud-based data sharing business model ensures that data is democratized across the entire organization, as well as its partners.

3. Built-in Activity Tracking

Cloud-based data sharing through data platforms such as Revelate automatically track data sharing activities, including who accesses what data sets, when, and from where. Revelate’s white-label data web store tracks every action, allowing you to quickly identify security gaps, implement changes and improvements to security measures, and determine whether access settings need to be adjusted. For instance, you can set up your web store to only allow access to certain data sets during a set period of time and only to those with certain access permissions.

4. Allows a Better Understanding of Trends

Since cloud-based data sharing better facilitates on-demand access to data, trends that affect business processes and contribute to growth can be better understood by using the latest available data, whether that data is coming from external or internal sources. This allows organizations to be more proactive in terms of anticipating how their customer’s behaviors will affect organizational goals, such as sales.

5. Enables Organizations to Embrace Data Sharing as a Product

Data sharing through cloud-based allows organizations to embrace data monetization, which provides an additional revenue stream while at the same time not putting any additional pressure on IT teams to fulfill data orders manually. With a data web store through Revelate, for instance, data orders can be easily fulfilled via self-service, salespeople, or other individuals in the organization.

6. Enhances Business Efficiency

When stakeholders can access the data they need when they need it, it improves business efficiency. Rather than needing to rely on IT, data scientists, or other technical individuals in an organization, cloud-based data sharing facilitates easy access to the data that people need to make data-driven business decisions.

Simplify Data Fulfillment with Revelate

Revelate provides a suite of capabilities for data sharing and data commercialization for our customers to fully realize the value of their data. Harness the power of your data today!

Get Started

Situational Trust Framework for Data Sharing in Business

Situational Trust Framework for Data Sharing in Business

Data Sharing Trust Framework Step Description
      1. Identify data sharing use cases Collaborate with stakeholders to determine use cases for data sharing that can drive further value in terms of business outcomes
      2. Identify perfect levels of trust Determine what would resources, tools, technologies, etc., would be required to ensure a “perfect” level of trust
      3. Identify situational levels of trust Determine levels of trust that would match the use cases outlined in the first step, and consider the risk-reward of “imperfect” data use in these scenarios and in future scenarios
      4. Remove elements of trust that are in misalignment of situational trust Consider what trust initiatives are unsustainable/unobtainable in terms of resources, tech, etc., and consider what’s needed to reach situational trust

Building a trust framework for data sharing in business is extremely important to stifle fear-based objections and create an understanding that situational trust—that is, trusting individuals and organizations in a data sharing network with data based on the situation, like the use-case scenario and future business opportunities, rather than focusing on creating a data sharing utopia.

Building situational trust in terms of data sharing in business requires consideration of the following:

Demonstrating the Necessity of Data Sharing in Business

There’s no doubt that data sharing is key for today’s businesses, but demonstrating that necessity is paramount, and that means achieving stakeholder engagement and ensuring that the right access to the right data is prioritized. According to Gartner, automated trust metrics across internal and external data ecosystems are poised to replace most other solutions, which will result in halving data sharing risk.

Establish Situational Trust Across Data Sharing Ecosystems

It’s imperative that Data and Analytics leaders understand the importance of building situational trust across data sharing ecosystems rather than focusing on building a perfect level of trust. Perfect trust, just like trying to perfect anything else, can either be unobtainable or unsustainable—especially in a data sharing environment with multiple players and ecosystems.

Building out secure data sharing protocols complete with security and access privileges is important, but aiming for perfection often means an overinvestment of resources, time, and money for little return, so a balance must be struck between the two. This often means focusing on the context behind why a data consumer wants a particular dataset and making decisions situationally rather than having a blanket policy for data sharing.

Utilizing The Data Sharing Business Model to Accelerate Business

Specific use cases for certain datasets may be obvious, but it’s worth taking another look and seeing if use cases can be expanded to additional industries, partners, and teams. This helps drive value for datasets while at the same time encouraging a growth mindset.

How Revelate Supports Effective Data Sharing

How Revelate Supports Effective Data Sharing

Through Revelate, data sharing is made easy regardless of who wants to access datasets. By significantly reducing pressure on technical and IT teams to fulfill data orders and instead democratizing the responsibility across departments, effective internal and external data sharing can be realized.

Here are some scenarios:

  • An organization has several departments (e.g., marketing, finance, customer support) that often request datasets to create reports, review customer acquisition and service initiatives, or to determine how to improve existing processes. In a typical scenario, IT would either provide large, unorganized datasets that would require extensive time and resources to sift through, or IT would take on the burden of information isolation before sending.
  • An organization that used to deal with only a few data orders per month is now getting hundreds of requests for data orders—requests that simply can’t be fulfilled manually by IT teams, as it’s much too resource-intensive.

In both cases, Revelate is able to automate the data fulfillment process so that whoever needs access to datasets can get it, whether it’s one user at a time or hundreds. Using previously set out security and access requirements, Revelate automates data extraction, preparation, processing, and finally distribution to the relevant data customer. Using a fully customizable web store, you can control not only what data can be accessed but also when and who accesses said data without having to lift a finger.


Building an effective data sharing business model is a must for modern businesses. If you’re interested in learning more about how you can add efficiency and security to your organization’s data sharing initiatives through a secure, automated platform, reach out to Revelate today to Book a Demo.

Simplify Data Fulfillment with Revelate

Revelate provides a suite of capabilities for data sharing and data commercialization for our customers to fully realize the value of their data. Harness the power of your data today!

Get Started