For a large global organization, having data available in Collibra is only half the battle; users must be able to access it efficiently. The client had an existing, rudimentary implementation of a marketplace, but it was fragmented and difficult to navigate. Users often hit dead ends, having to trigger multiple separate workflows just to get access to related datasets. With support from Murdio’s technical implementation team, the client overhauled this experience, delivering a “future-proof” Data Marketplace that handles complex logic behind the scenes while keeping the front-end experience simple and intuitive.
The challenge
The client already utilized Collibra but struggled with a “patchwork” approach to data access. Their existing solution consisted of disjointed workflows – a user might finish one process only to realize they needed to navigate to a different asset to trigger the next step. There was no cohesive “shopping” experience.
This fragmentation caused frustration for business users and generated a significant support burden for the Data Governance team, who were constantly fielding questions from confused employees. Furthermore, the client wanted to future-proof their architecture. While they currently focused on granting access to tables and reports, they needed a solution capable of handling “Data Products” in the near future without requiring a system redesign.
The technical requirements were high: the organization had a complex governance model where different assets required vastly different approval paths (ranging from auto-approval to external system validation), all of which had to be handled within a single “shopping cart” request.
The solution
Murdio deployed a focused two-person team – a Solution Architect and a Senior Developer – who collaborated closely with the client’s Data Governance Lead over a six-month period. Unlike projects requiring extensive business workshops, this engagement focused on executing a specific, highly technical vision defined by the client’s Product Owner.
Key capabilities delivered included:
- Unified end-to-end experience: The team replaced the disjointed workflows with a single, end-to-end process. The new interface acts as a guide, navigating the user from initial selection to checkout. It includes “waiting tasks” and informative pop-ups so users always know exactly what the system is doing, even during API calls.
- Complex “mixed basket” logic: The standout feature of the solution is its ability to handle a mixed shopping cart. A user can request 50 different assets at once. The system automatically splits them, routing 10 to auto-approve, 20 to specific data owners, and others to external systems, while keeping the user informed via a summary screen (e.g., “17 items will require approval, 10 are auto-approved”).
- Automated provisioning integration: The team built scripts to handle the “last mile” of access. Once approvals are secured in Collibra, the system triggers external APIs to provision access in source systems, waiting for a success response before closing the ticket.
- UX optimization & “fail-fast” checks: To improve usability, Murdio implemented “auto-reject” checks at the start of the process. If a user selects an asset that is configured to automatically reject their specific profile or use case, the system warns them immediately, preventing them from wasting 15 minutes filling out forms for a request that is doomed to fail.
Outcomes
The new Data Marketplace is now live in the production environment, serving as the single point of entry for data access.
Streamlined user experience: The “patchwork” experience has been eliminated. Users can now browse, add multiple assets to a cart, and check out in one seamless flow. The interface guides them step-by-step, significantly reducing the “how-to” questions previously directed at the governance team.
Scalable & future-proof: The solution effectively handles the client’s complex approval matrix, ensuring strict governance without slowing down the user. Crucially, the architecture was built to support the client’s transition to Data Products, ensuring the investment remains valuable as their data maturity grows.
Automated efficiency: By integrating directly with provisioning systems and automating the routing of requests, the client has reduced manual intervention and sped up the “time-to-data” for business analysts and data scientists across the organization.
