If you’ve worked in an SAP enterprise, you know this dynamic well. SAP systems generate massive volumes of business-critical data, from ERP and CRM to supply chain, HR, finance, and operational reporting.
SAP’s HANA-based applications are really comprehensive and powerful, but their native tooling focuses primarily on operational processes and storage. They don’t inherently give a complete, business-friendly view of data governance across all data sources, especially when you bring in non-SAP systems, cloud platforms, analytics tools, or AI models.
This often creates a core challenge:
Without that layer, enterprise teams struggle to answer basic questions around:
For SAP-powered enterprises, where upwards of 80% of mission-critical operational data originates from SAP applications, a system of engagement for data intelligence is the prerequisite for digital transformation.
And Collibra is a great candidate. It provides the governance foundation that operational SAP landscapes lack, especially as enterprises modernize their data and AI strategies. And when you connect the two – that’s when data governance happens. (Because it’s definitely not magic. Actually, it’s Collibra Edge, acting as a bridge and providing a secure, scalable runtime environment that resides within the organization’s own network, whether on-premise or in a private cloud.)
One of the core concepts SAP and Collibra unanimously emphasize is a business data fabric. This might seem like a buzzword at first – but it’s really more than that. An architectural approach that stitches together data from varied sources (SAP and beyond) into a governed, searchable, and trusted mesh.
A business data fabric does three things well:
Collibra integrates deeply with SAP data platforms like SAP Datasphere and SAP Analytics Cloud, bringing SAP metadata and assets into Collibra’s governance view. This means data assets – tables, columns, models, and relationships – sync into Collibra’s data catalog and intelligence platform, making them discoverable and governable alongside non-SAP assets.
This unified fabric is particularly important as you scale your AI initiatives, migrate to SAP S/4HANA, or modernize your analytics environments. When there’s no unified governance layer, data remains fragmented across tools and teams. And this means decision-making slows down and data risks go up.
And the risk is not that SAP data is wrong. It’s just that once SAP data is reused for analytics and AI without governance, errors, misinterpretations, and compliance issues scale faster than humans can detect them. And that leads to all sorts of consequences, including failed audits, misleading AI outputs, and inadequate business decisions – even if the data technically looks “fine” on the outside.
AI adoption is exploding, but it’s also exposing a major data governance gap: enterprises can’t blindly trust the data fueling AI models. Without comprehensive AI governance, automated lineage, quality checks, and business context, AI projects might produce biased, inaccurate, or non-compliant outputs.
This means that if you don’t know your data thoroughly (and we mean, thoroughly), you can accidentally share high-risk data that AI should never be able to access.
Collibra’s governance layer addresses these risks by:
All this gives organizations higher confidence when driving AI initiatives, which otherwise slow down progress because there’s no governance or trust in data.
Typically, migrating to SAP S/4HANA is one of the biggest transformations for SAP enterprises. And it’s not just code or infrastructure that’s the challenge. Of course, it’s also data and governance. Poor data quality, unclear lineage, inconsistent metadata – they all complicate cutovers and – more often than not – drive costly rework.
While Collibra doesn’t migrate systems for you, it provides tools such as:
When there’s no unified governance layer, S/4HANA migrations can become more manual and thus, error-prone – because teams can’t easily verify which data is accurate or fit for purpose.
The enterprise struggle with legacy governance is real.
And data quality tools were never designed for the scale or complexity of modern data landscapes. Tools like older data quality platforms or homegrown spreadsheets become blockers because they:
Collibra offers a centralized platform that can ingest metadata and quality signals from across SAP and non-SAP tools, surfacing governance issues in one place and enabling coordinated remediation. And eliminating disconnected, outdated, and ineffective tooling.
The SAP and Collibra partnership has evolved over recent years from early strategic alignment to practical, native integrations, connecting metadata and governance workflows between SAP’s data platforms and Collibra’s enterprise governance tools.
Since 2024, SAP has also been using Collibra for reusable, governed data products. With flexible asset modeling, tailored workflows, and deep integrations across SAP’s data ecosystem, Collibra helps SAP operationalize and streamline access to high-quality data.
Here’s what they say about it:
“Digital transformation starts with data you can trust – quality is non-negotiable. With Collibra Data Quality & Observability, our customers can ensure the accuracy, completeness, and reliability of their data, establishing the foundation needed for confident, relevant, reliable and responsible AI.”
Irfan Khan, President & Chief Product Officer, SAP Data & Analytics
Let’s walk through the key SAP products that integrate with Collibra.
SAP Datasphere serves as the foundation for a business data fabric. Collibra’s integration with SAP Datasphere allows metadata, including tables, views, columns, models, and perspectives, to be ingested into Collibra’s data catalog, helping discover SAP Datasphere assets inside Collibra, and providing broader governance and traceability across SAP and non-SAP systems.
Through the SAP Datasphere Catalog, metadata from SAP Analytics Cloud (SAC) is also made available in Collibra. What this means in practice is that your BI and analytical metadata are governed and tracked alongside operational data models, giving you a more holistic governance view.
Collibra can connect to SAP HANA Cloud databases through supported connectors, pulling metadata, performing profiling, and enabling data quality jobs.
Collibra’s Data Quality and Observability features allow automated checks, monitoring, and alerts, giving teams confidence that HANA-resident data is accurate and compliant for downstream usage.
(This is a common integration pattern – Collibra’s Edge application often retrieves metadata via JDBC or native connectors from HANA systems and catalogues it for governance and quality.)
Also, read our case studies on custom integrations we built for our clients:
SAP’s Business Data Cloud (BDC) now has a native integration with Collibra Data Quality & Observability, giving joint customers the ability to run 10× more active data quality jobs on BDC data and monitor quality metrics across business datasets.
According to Collibra’s Founder and CEO, Felix Van de Maele:
“SAP BDC gives customers a powerful data platform to unify SAP data and develop transformative AI. Collibra Data Quality & Observability supplements SAP BDC by monitoring, validating and sending notifications for data modeled and transformed within SAP BDC, giving customers complete confidence in the data feeding their AI.”
SAP has also created migration accelerators for customers moving from SAP Information Steward to Collibra’s Quality and Observability suite, ensuring governance continuity and minimizing disruption.
SAP LeanIX focuses on enterprise architecture and application portfolio management, including landscape rationalization and process documentation. It can complement Collibra by providing architectural context and alignment with governance initiatives.
Collibra and LeanIX aren’t native metadata integrations in the same way as Datasphere, but their joint use enhances the governance and architectural ecosystem. The integration helps align data architecture (in Collibra) with enterprise architecture (in LeanIX), so teams can see how data assets relate to technology and business capabilities.
And by linking the technical and architectural context, it improves metadata quality, transparency, and accountability.
Let’s break it down into several aspects.
Collibra is designed as a unified governance platform across SAP and non-SAP systems, providing metadata management, quality, lineage, stewardship workflows, business glossary, policy automation, and AI governance.
SAP’s native tools focus more narrowly within the SAP ecosystem, e.g., MDG handles master data consolidation and rules, and Information Steward focuses on profiling/quality within SAP landscapes.
Collibra’s strength lies in enterprise metadata management and automated lineage across sources, giving a global view. SAP native tools typically lack comprehensive cross-system lineage for analytics and data governance beyond SAP. Collibra fills that gap for heterogeneous environments, making integration much easier between SAP and non-SAP systems.
Collibra’s governance workflows, role-based dashboards, and stewardship management are robust and built for enterprise-scale governance across teams. SAP’s native tools are powerful for master data and specific profiling tasks, but aren’t designed as a centralized governance hub for hybrid landscapes.
Collibra’s cloud-centric governance tools tend to be easier for business users and broader governance teams to adopt. Though what’s really important here is to really zero in on adoption right from the start of implementation. Hiring the right Collibra Service Partner is the key here.
SAP Information Steward may be easier to set up initially, but lacks broader governance depth.
| Feature | Collibra unified platform | SAP Native Tools (MDG / Information Steward) |
| Primary Focus | Centralized, enterprise-wide governance across SAP and non-SAP systems. | Operational master data management and profiling within the SAP ecosystem. |
| Data Lineage | Automated, cross-system lineage showing data flow from any source to BI/AI. | Narrow lineage, typically focused only on technical flows within SAP landscapes. |
| Business Context | Robust business glossary and stewardship for non-technical users. | More technical metadata focus, often harder for business teams to adopt. |
| AI Governance | Dedicated AI governance to manage models, usage, and ethical compliance. | Limited; focused primarily on the data quality feeding into the systems. |
| Integration | Acts as a “system of engagement” for a heterogeneous (hybrid) data fabric. | Best-in-class for managing data inside SAP, but often siloed from external cloud apps. |
As with any enterprise tools, it’s really not just about the software itself – tool integrations often demand process transformations across the enterprise, and it’s usually much more complex than just a ready-made integration. And that’s what we’re here for at Murdio – to facilitate this and help bring value faster, in the least complicated way.
Like we did for one of our clients – a leading international retail organization – for whom we implemented custom Collibra SAP lineage.
The company faced challenges in tracking and understanding the lineage of critical data attributes such as total shelf life across its complex data ecosystem. And in retail, it’s pretty common to face the challenge of tracing a customer’s journey and accurately attributing sales across a complex landscape of systems, especially with core platforms like SAP.
We developed a transformative solution to address the challenges of tracking and understanding data lineage through a sophisticated technological infrastructure that spanned SAP Master Data Governance (MDG), SAP Business Warehouse (BW), SAP ERP, centralized data lakes, and Collibra business intelligence platforms.
Our work included:
And because we always start with adoption in mind, projects like this are more tailored to your organization’s specific needs and designed to bring results faster, with access to the cross-industry expertise of the entire team of certified Collibra experts at Murdio, even if you’re just working with one.
We’re the only Collibra consulting and implementation company with 14 Collibra Rangers on board. A Collibra Ranger is not just a consultant. They’re technical specialists with over six years of experience in solving the most intractable data governance challenges. And this level of expertise is critical when dealing with SAP’s often poorly documented or customized technical metadata. We combine out-of-the-box solutions (e.g., configuration of specialized integrators such as the ERP/CRM Integrator) with deep technical expertise to build custom integrations where standard tooling is not enough.
Our team includes specialized roles that address every aspect of the implementation:
Read more: Case study: Custom Collibra SAP lineage implementation.
And here’s another helpful read: How to improve data quality in retail
A business data fabric is more than a nice-sounding phrase. It supports analytics, compliance, operations, migrations, and AI – and you can build it for your enterprise by integrating SAP’s enterprise-grade data platforms with Collibra’s governance and intelligence capabilities.
If your enterprise is modernizing its SAP landscape, scaling analytics, or pursuing data-driven innovation, we can help you turn data governance from a blocker into a competitive advantage and a business enabler. We’ve successfully delivered SAP + Collibra integrations for global organizations.
Schedule a chat with our experts to talk about your SAP-Collibra challenges.
No. SAP and Collibra are complementary. They solve different problems and are designed to work together.
SAP focuses on:
Collibra focuses on:
No, even SAP-centric organizations benefit from Collibra. Most SAP enterprises still struggle with:
Collibra adds value even in heavily SAP-based landscapes, and becomes critical once non-SAP tools, cloud platforms, or AI use cases are introduced.
No. Collibra does not replace SAP MDG. In mature setups, MDG and Collibra coexist, each serving a distinct role.
Yes, indirectly, but importantly.
Collibra does not migrate systems, but it helps reduce migration risk and post-migration surprises by:
Collibra ingests metadata from SAP Datasphere and SAP Analytics Cloud, including:
This metadata is then governed alongside non-SAP assets, giving teams a unified view of enterprise data.
AI scales both value and mistakes.
Without governance:
Collibra adds quality checks, lineage, ownership, and usage controls that make SAP data safer for AI.
Primarily, yes, but not exclusively.
The SAP-Collibra alliance delivers the most value where:
That said, mid-size organizations planning growth or cloud migration benefit from putting governance in place early.
3 March 2026
| Collibra
2 March 2026
| Collibra
17 February 2026
| Case Study
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