Operationalizing data products means establishing clear, enforceable processes and guardrails that let teams reliably build, access, and trust data products without reinventing foundational decisions.
Witboost streamlines this by embedding standards, clarifying ownership, and guaranteeing asset quality—so teams can focus on delivering value, not chasing decisions or fixing broken data.
At Witboost, we've been building our data product management platform for years. And throughout this journey, one question has consistently come up:
If all customers face the same challenges and solve them in similar ways, why should platform engineers repeatedly reinvent the wheel?
Sure, the problems are not identical, and neither are the solutions. But we operate within the same problem space, and the engineering mindset we apply is often the same.
From a methodological perspective, these challenges can be approached similarly, and the knowledge accumulated along the way should be reused instead of being rebuilt each time.
This is what we mean when we talk about operationalizing data products.
Operationalizing data products means having a clear, structured process for turning a use case into something that can be built and run. It requires knowing exactly how to manage the entire lifecycle of a data product:
But that’s not all. What we value most about operationalization is the ability to shape the platform around the human thought processes that move us from shared problems to tailored solutions.
We have identified three main categories of challenges that consistently emerge. We'll explore them in this piece and show how we address each one with Witboost.
1. Dealing with standards
The most common reason for losing control of data platforms is the lack of standards.
Standards operate at every level of a platform: system design decisions, technology-specific policies, as well as communication and shared terminology.
When designing a platform, you always need to make many decisions spanning a wide range of very different topics. For example, do we want to establish a naming convention for platform resources? Which encryption algorithm should we use? Or simply but fundamentally: how do we just call things?
A platform is usually populated by different stakeholders: engineers, product owners, functional analysts, and so on. One of the most basic reasons platforms become complex and inefficient is the absence of a common glossary.
Different stakeholders use different levels of abstraction when communicating. So even a common vocabulary is a decision to be made—and let’s be honest, no one makes it.
All these decisions are hard to make at first, and hard to stick with over time. As for the first part, Witboost or not, you must make these decisions yourself. The goal of Witboost is to ensure your decisions are respected, but it won’t make them for you.
At this stage of building a platform comes the most tedious part for human beings: writing down the decisions that were made and asking users to read dozens of pages of documentation. Spoiler alert: that never happens.
From a standards perspective, operationalizing data products does not mean periodically checking users’ actions or reviewing the status of the resources they create.
It means enabling people to do only the right things by design:
- You don’t need to raise an exception if someone breaks a naming convention. You can’t break it if you create resources through Witboost.
- You won’t receive an email from the security team because you used the wrong encryption algorithm. This simply can’t happen if you create your storage through Witboost.
- You will call the place where you store your data “the NoSQL database” instead of “storage area”, so everyone at the table will be able to discuss platform issues using the same language.
What Witboost guarantees that these kinds of guardrails are respected, but the effort of implementing guardrails is still there.
Wait: so, you’re telling me that I must implement stuff anyway, so... why Witboost?
It’s a matter of paradigm shift. Creating and managing resources via Witboost embeds all the guidelines that should be written down on paper, without the need to actually write them or read them. Your organization’s needs now live and evolve together with the platform.
2. Hunting Down Data Owners
Once the guidelines to run your platform are decided, it’s time to start the next step: onboarding the first users.
Who are the users of a platform? A platform user is someone who needs to implement a new use case by combining the existing components that the platform provides with some new business logic.
Let’s take an example with the most common component a platform exposes: data.
Here’s what you want to achieve:
1. Building a workload within the platform that reads one or more datasets exposed by other teams
2. Joining them in some way
3. Applying your brand-new business logic
4. And producing some KPIs
This sounds straightforward until you find yourself unable to answer some questions that block development for days or even weeks: where is the data? How do I contact the data owner to obtain access?
This is where the platform starts addressing an organizational problem.
One of the most underrated yet key problems to solve is chasing data owners down. Streamlining that process can dramatically speed up the journey from idea to production.
So in operationalizing data products with Witboost, you are identifying data asset owners and requesting access to the resources they manage. This is a core part of creating a new data product and it all happens under the hood.
A data asset cannot exist within the platform without an associated owner. And once you have an owner and an automated mechanism to request access, you’re all set!
This reasoning assumes you already know which data you need. If you don’t, Witboost makes visual discovery easy, letting you navigate through your organization’s assets and find what you need.
And if your organization is too complex to explore visually, Witty (an AI-powered assistant) is always available to answer questions like: “I need to compute this KPI. Which assets do I need from the platform?” and guide you to the right ones. It's as simple as that.
3. Validating what you got
Once you have your standards in place, you know where to find what you need. Once you know how to request access to the asset you need, you’re almost there. So, what could still go wrong?
There’s one final step that developers (and platform users in general) have always relied on: validating what they received.
You’ve just been granted access to the data required for your brand-new use case, and the first thing you do is inspect it to ensure it contains exactly what you expect. You verify that the data is accurate and not corrupted so that you can confidently build on top of it.
We’ve all done this at least once. It’s reasonable not to trust any system by default when we lack guarantees. This “zero-trust” mindset helps us avoid unexpected issues. However, it can also result in significant wasted time.
If the data is correct, the loss is negligible. But if it isn’t… that’s when the nightmare begins.
You go back to the data owner, request clarifications, and they begin investigating with their team. Meetings get scheduled, fixes are planned, and suddenly you’ve lost control over quality and timelines.
With Witboost, we aim to operationalize these validation checks for all assets within the platform. Witboost enables you to establish a foundation of trust and rely on the data after access is granted — without needing to manually re-validate everything each time.
Corrupted assets simply cannot exist by design in Witboost.
Think of it like buying food from a grocery store: you walk through the shelves, pick what you need for dinner, and go home.
In a traditional or smaller store, there’s always a chance that a product on the shelf has expired and could be harmful. You might only discover it once you’re home — and then you have to go back, complain, and replace it (or buy something else, as you still need alternative food for dinner). That’s a significant waste of time.
Conclusion
With Witboost, we aim to recreate the convenience of that experience without the risk. It’s like shopping in a store where every single product is guaranteed to be fresh and safe. You don’t need to check the expiration date: the platform already ensures it meets the required standards.
Of course, you can still validate the data if you want to, but you gain peace of mind when you get to work. No surprises, no rework, and no time lost chasing down fixes. You can simply trust what you receive and focus on building value.