Solve these 5 problems and your data users will love you

If you care about how data is used in your organization, you need to understand the heartbeat of your data ecosystem: its users.

Beyond algorithms and dashboards lies a critical truth: the real magic happens when you create an environment where data isn’t just collected, but truly understood, shared, and leveraged.

If you want to know if you’ve succeeded, you just need to talk to the end users of data, those making decisions that impact the business. The answers aren’t always pretty. Many users don’t even know what data exists, let alone how to access it. The good news is that these issues are solvable. However, the way that organizations typically go about solving these issues tends to result in solutions that are highly complex and inflexible. Here’s how to do it better. Here’s how to make your data consumers happy.

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1. Making data discoverable

The journey often begins with a foundational question: What data do we have, and where is it? Data is often scattered across the organization, in different places and formats, making it hard to find and trust. Without clear visibility, data consumers can’t confidently locate what they need.

A comprehensive data catalog provides an organized view of all data assets. It empowers teams to quickly find and understand what data is available, going some way to bridging the gap between discovery and usability. Most large organizations already have a catalog of some description, and some even have several catalogs running in parallel. But as industry expert Wayne Eckerson says, “​​a data catalog gets users halfway to data, while a data marketplace closes the loop.” Once users can see all the relevant data, what happens when they start asking for access?

2. Gaining approval to access the data

Even if data is found, getting access is often a slow, frustrating process. Reviews and approvals can hold up projects and derail timelines. Governance is clearly a necessity to mitigate risk, but automating this process is key to avoid bottlenecks and delays.

An efficient, scalable permissioning system can make access faster without compromising security. With role-based access, data owners can approve requests promptly, helping teams get what they need without the wait. Permissioning can be handled by some data catalogs, but is a core feature of a data marketplace. Ultimately, the goal here should be to provide governed access and use of data assets. A data marketplace does precisely this.Now that your users have discovered and accessed the data, you’ve got another problem to solve. How do they do anything with it?

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3. Deploying/accessing infrastructure to consume data

Once access is granted, the typical user experience is anything but self-service. Connecting relevant storage and tools is time-intensive. Not every system works well together, and migrating data between infrastructure can be prohibitively expensive or otherwise impractical. Formatting data to work with BI and analysis tools often requires data engineering work. Building custom integrations and pipelines is often time consuming and expensive. In fact, Wakefield Research suggests that custom data pipelines cost an average of $520,000/year to maintain, with even simple pipelines taking an average of between 3-4 weeks of build time.

Ultimately, it’s all about providing the right user experience for the job — analytics, BI tools, or distributing the data to another system. A data marketplace is a great way to provide such an experience, providing flexible access to data and tools for any type of user. Capabilities of a data marketplace include connectors (for self-service pipelines), data product management, subscriptions, export, and many others.Now, if you’ve made it this far, give yourself a pat on the back. You are already way ahead of most organizations. But to truly unlock high value use cases — and make this work repeatable and scalable — there are two more steps: customization and collaboration.

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4. Customizing data for specific use cases

Data needs vary by use case and by user. Offering ways to customize data — whether through filtering, sorting, joining, transforming, reformatting, etc. — can enable data users to get to a valuable outcome quicker. Cloud data platforms like Databricks, Snowflake, Google BigQuery, Azure Blog Storage, and Amazon Redshift offer some ability to customize data, but options are limited when data is stored across multiple different platforms and providers. Additionally, these customizations tend to require certain technical abilities, so some users will need to enlist the help of data engineers to achieve their goals.

Flexible tools (like a data marketplace) allow users to adapt data to their needs without additional resources. With built-in controls, query engines, and filters, teams can customize data safely, minimizing delays and empowering self-service to even non-technical users. Data owners can apply restrictions to prevent data misuse, or impose limits on compute to keep cloud costs under control.

Now that you’ve empowered users with exactly what they need, how can you help them work together?

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5. Collaborating across internal and external teams

Collaboration — across teams, departments, business units, and organizations — on data projects can unlock immense value, but remains challenging. Collaborating responsibly and efficiently can be tough, especially when data needs to cross departmental or organizational boundaries.

To empower your data users to collaborate at scale, they will need secure (or zero-trust) collaboration tools. Robust sharing tools, with row- and column-level restrictions, make collaborating on data products simple. Again, a data marketplace can solve this. Because governance is integrated at every level, data owners can control which users can access sensitive data and what they can do with it. An example here would be wanting to share dashboards or views with an external party without exposing any underlying data to them. With governance and permissioning at the core, risks associated with collaboration are controlled.

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Putting users at the heart of your data strategy

By putting users at the center of your data strategy, you will create more than just efficient processes; you’re building a foundation for smarter decision-making at every level of your business. The most successful organizations won’t be those with the most data, but those who best understand how to listen to their data, empower their users, and turn potential into performance. Your data is waiting — are you ready to unlock its full story?