Building vs Buying your data product marketplace: 10 common misconceptions

Businesses are increasingly turning to data product marketplaces to share their data more widely across the organization and unlock its value. Data product marketplaces aim to provide a centralized space for data access for everyone, breaking down silos and increasing usage and collaboration.

However, data marketplaces are an emerging technology category. This means that many organizations are unsure whether the best deployment approach is to buy from a specialist third party vendor or build their own solution internally. There are a range of common misconceptions around the build versus buy debate – this blog explains them to help organizations make the right choice for their data marketplace project.

False.

From the outside it may seem that a data marketplace is simply a web-based front end to your data, making it easy to build internally. However, creating a data product marketplace that doesn’t just provide data, but drives consumption, is much more complex.

Building this type of solution needs specialist skills that may not be available within the organization, or that may be better deployed on other projects. Once the solution is created it then needs to be supported, maintained, and updated, adding to IT time and cost. All of this means that internal solutions can end up being more expensive and resource-intensive than buying a SaaS based data product marketplace solution from a recognized expert vendor.

False.

It is true that building internally means the data product marketplace is completely personalized to the company’s needs and business priorities. It can be created to match corporate look and feel in terms of the interface and design, helping drive recognition and adoption by staff.

However, the greater the tailoring required, the longer the development process is likely to be, risking missed deadlines and lowering ROI. Buying an external solution that can be customized to your needs enables you to align the data product marketplace with business priorities while deploying more quickly. Working with an experienced vendor ensures you get a best-of-breed solution that has already been deployed in hundreds of similar organizations, lowering time to value by speeding up deployments.

False.

Failing to protect data effectively leads to compliance issues, potential regulatory breaches and reputational damage. Consequently, ensuring that data is secure, well-governed, and is only accessible by the right people is a key requirement for organizations. Building your own solution can deliver control, but often at the cost of reducing access to data, hampering its usage across the business.

Instead, buying a SaaS data product marketplace solution maximizes protection while enabling data sharing. Look for a vendor that offers comprehensive, granular access management capabilities, a full audit trail, integration into your corporate security infrastructure (such as by allowing SSO and MFA), and secure cloud hosting by recognized vendors. This will deliver the required security, while minimizing administration time and resource.

False.

It’s important to look at the total cost of ownership (TCO) when making the build versus buy choice. SaaS vendors offer usage-based billing, meaning your costs are constant and predictable. In contrast, building your own solution requires internal development time and resources, often pulling people from other projects.

Once the solution is live it then needs to be hosted, supported and maintained, bringing ongoing, long-term costs to the business. So, even if the initial deployment is cheaper, the total cost over the lifetime of the project will be higher if you go for the in-house option.

False.

As data volumes have grown, and requirements have changed, organizations have created increasingly complex IT and data infrastructures. Consequently, there can be concerns that integrating another third party solution will be difficult and require infrastructure changes to work effectively.

However, SaaS data product marketplaces are designed to integrate seamlessly into existing solutions, with vendors offering a range of connectors and APIs to ensure data flows effectively across the organization. They also have experience at deploying solutions in complex environments that helps speed up projects and ensures integration success. Only the biggest, and most complex, organizations with large-scale IT and data teams will benefit from building rather than buying their data product marketplace. 

False.

Adoption of any IT solution is critical, particularly when it comes to driving greater access and consumption of data. That’s why simply building a central data space that is difficult for employees to use won’t deliver consumption or value. Instead, to ensure that employees engage with your data, and access and consume data products and other assets requires an intuitive, e-commerce style experience.

The interface has to be as simple as an e-commerce website, with features such as AI-driven natural language search to encourage usage, and active metadata management to help AI models and agents find the right data. External vendors offer these features in their solution, and back this up with deep experience of how to drive long-term adoption. This means that buying, rather than building, is likely to maximize engagement and usage.

False.

Organizations have large – and ever-increasing – volumes of data, from a growing number of sources. The concern is that as more and more data is added to the data product marketplace, and usage increases, external systems will not be able to perform adequately. In fact, their cloud-based nature and scalable design mean they can cope with potentially enormous volumes of both data and users.

At Huwise we’ve seen this in action. During the Paris 2024 Olympics, the organizer’s Games Map, powered by Huwise, saw millions of unique users, generating spikes of more than 200 requests per second at its peak, without impacting performance. Additionally, building and hosting on-premise means that more IT resources are needed as usage increases, further adding to costs, and potentially hitting performance if resources cannot be deployed quickly enough.

False.

Implemented successfully, building in-house will deliver an ultra-tailored solution that differentiates a business from its competitors. However, this requires significant, long-term investment, deep technical resources, a highly integrated technology environment, and an

ultra-specific business need that is difficult to address with a standard solution. Lead times are likely to be longer, the project will be more expensive, and risks around slipping project timelines and feature creep much higher. For the majority of companies, buying and adapting a third-party solution will meet all of their needs and enable them to quickly create value through increased data consumption, while controlling cost and risk.

False.

Successful AI relies on good, contextualized and trusted data, something that many projects have struggled with. A data product marketplace provides AI with access to relevant, understandable data that can power AI use cases. Building a solution internally that delivers this access requires key skills and capabilities around metadata management and semantic and context layers.

This can be complex and time-consuming, particularly as many AI skills are in short supply. Instead, partnering with an external vendor that offers these capabilities, as well as features such as a Model Context Protocol (MCP) server, means that the solution automatically ensures that data is AI-ready. This frees up employee time to focus on AI implementations, rather than data plumbing, maximizing the positive impact of AI projects.

False.

Often organizations don’t currently possess the right skills in-house to build and then maintain a data product marketplace. Recruiting new staff or retraining existing employees can bridge this gap. However, it will add to costs, particularly as many skills may not have a wide applicability in other areas.

Additionally, relying on a small number of technical specialists can cause issues if they leave, resulting in gaps in your knowledge and increased risk. Working with an external vendor enables employees to focus on key tasks and roles. They can collaborate with the business to understand their needs, manage the creation of relevant data products, maintain them over time and focus on driving usage and engagement. This focused approach delivers greater ROI by directly increasing consumption.

As with every IT solution, organizations need to carefully weigh up the different benefits and risks of building in-house versus buying from an external vendor. Senior leaders need to understand common misconceptions and base their decision on the factors that matter most to their organization and its strategy. Except for the largest organizations with the most complex needs, analysis and experience points to buying as the optimal choice when deploying a data product marketplace, delivering greater value, lowering risk and maximizing the usage of internal resources.