SAP systems are the beating heart of many organizations, managing everything from financial transactions to supply chains and customer relationships. These systems generate a staggering amount of data—data with the potential to drive innovation, streamline operations, and create a competitive edge. Yet, if you're like most SAP customers, that potential remains untapped.

Instead of fueling transformation, much of this data sits locked away, inaccessible and underutilized. In this blog series, we’ll explore the challenges and opportunities SAP customers face when it comes to their data. From navigating the complexities of traditional SAP data solutions to leveraging modern platforms like Microsoft Fabric, we’ll chart a path toward unlocking the true value of your SAP data.

Whether you’re struggling with siloed reporting, outdated tools, or simply wondering where to go next, this series is your roadmap to rethinking what’s possible with SAP data. Let’s get started!

The Hidden Potential of SAP Data

SAP has historically claimed that around 77% of global transaction revenue eventually touches an SAP system—a staggering statistic that showcases just how indispensable these systems are to the world's economy. However, there’s an unwritten corollary to this: nearly all of that data is destined to vanish into the digital abyss, never to see the light of day again, unless, of course, you count an occasional cameo in a quarterly compliance report.

Now, if you’re thinking, “Wait a minute, we have a ton of reports and dashboards lying around here,” let me stop you right there. Having an overflowing inventory of reports—whether in BusinessObjects, SAP Analytics Cloud (SAC), or some other tool—isn’t the same as getting value out of your SAP data. Indeed, the presence of multiple dashboards addressing the same (or similar) topics is usually a sign that your team isn't finding the answers they're looking for.

The real question is whether we're able to convert all that raw (but well-structured) SAP data into actionable, data-driven insights that help users make informed decisions. Visualizing data is helpful to a point, but our primary objective must always be to use data to drive smarter, faster, and more impactful business outcomes.

In practice, I’ve encountered very few SAP customers in my 25+ years working in the SAP space who feel they’re truly achieving their data goals. I’ve had countless conversations with SAP data architects and product owners who’ve shared their frustrations—pointing to the sheer difficulty of unlocking SAP’s treasure trove of data. It’s not that they lack the skill or ambition; it’s that SAP is a big, complex space with data that’s deeply embedded in intricate systems and processes.

Mining meaningful insights from it often feels less like tapping into a resource and more like navigating a labyrinth. It’s a challenge that requires more than just tools—you need a comprehensive platform that empowers users from across your entire organization to bring their knowledge and skillsets to bear towards harnessing the true potential of your SAP data.

Crossing the SAP Data Divide: What Comes Next?

These days, most of the SAP customers we talk to seem to be divided into two camps when it comes to their SAP data landscape:

• Sticking with the Status Quo: Customers in this camp are sticking with their existing enterprise data warehouse (EDW) solutions (at least for now). This includes customers running SAP Business Warehouse (SAP BW) and/or some kind of 3rd-party/home-grown solution.

• Moving to the Cloud: More and more, we're seeing customers migrating to cloud data platforms such as Snowflake or Google BigQuery. Although there are a variety of reasons for this shift, it mostly comes down to scalability and flexibility.

In either case, you could argue that customers from both of these camps are at a crossroads. Regardless of where these customers might be on their S/4 HANA journey, SAP data will continue to form a significant part of their overall data estate. However, with the explosion of SaaS solutions, Industry 4.0, and AI, SAP’s share of the overall data landscape has been steadily shrinking. This makes it more important than ever to take a unified approach to managing all that data.

Moving Beyond Data Warehouses

In a recent blog post, we talked about the importance of data consolidation and this is particularly true for SAP customers. Historically, if you were to ask an SAP customer to sketch out their enterprise IT landscape as a solar system, they'd probably depict SAP as this massive constellation with an unnatural and outsized gravity well. This line of thinking caused many of these customers to spin up an SAP BW system and then shoehorn in data from other systems where necessary.

Figure 1: An SAP Team's Perspective on the IT System Landscape

The problem with the "shove it all in the EDW" approach is that it fails to properly account for the avalanche of data coming from elsewhere within the business:

• Semi-Structured Data: As more and more SaaS and low-code solutions are adopted (e.g., Salesforce, Workday, and so forth), there's a need to integrate semi-structured data—that is, data that doesn't come directly from a relational database (SAP HANA or otherwise). Here, we're talking about the consumption of XML and JSON payloads from REST APIs, NoSQL databases, graph databases, or even data from log files or email messages.

• Streaming/Event Data: Besides the obvious streaming of sensor data in an Internet of Things (IoT) scenario, there's also event data flowing in from across the enterprise using various flavors of event grids (e.g., Kafka).

• Unstructured Data: Here, we're talking about all the unstructured data that orbits various business processes: attachments, images, audio/video files, free-form text content, and so forth.

While most customers have created data lakes (swamps?) to store this data, you really need to have all your data in one place to tell complete stories. Plus, if you have ambitions around data science and AI, having an all-in-one platform is essential.

These days, modern data platforms are providing the best of both worlds in the form of data lakehouses. Data Lakehouses combine the scalability and flexibility of data lakes with the performance and structure of data warehouses. They let you blend your structured data from ERP systems like SAP with semi-structured and unstructured data to support advanced analytics and real-time queries. This unified setup means you don’t have to deal with costly data duplication, and managing your data becomes much simpler—making it easier to uncover valuable insights from all your data sources.

Figure 2: Moving Towards a Data Lakehouse Architecture

From SAP BW to SAP Datasphere (and Beyond)

For SAP customers that are at that data platform crossroads, one of the pressing questions is whether it makes sense to stick with an SAP-centric solution, especially as an increasing amount of data that needs to be managed and analyzed comes from non-SAP sources.

While SAP's modern cloud data platform, SAP Datasphere, is naturally optimized for working with SAP data, its effectiveness in integrating and handling diverse data sources and catering to a broader audience of data consumers becomes a key consideration. Zooming out from SAP data wrangling and report development, it's essential to assess whether the platform can effectively meet your growing demands for cross-system integration and diverse use cases. This is where the Microsoft Fabric conversation becomes very interesting.

The Promise of Microsoft Fabric

Throughout the course of this blog series, we'll be unpacking some of the new and exciting ways that Fabric unlocks data-powered innovation. Not only does Fabric work seamlessly with SAP data, but it also empowers a wide range of data consumers across the organization—from analysts and data scientists to business users—to achieve so much more. By breaking down silos and enabling collaboration, Fabric ensures that everyone has the tools they need to turn data into actionable insights and drive meaningful outcomes.

Figure 3: Microsoft Fabric as an All-In-One Data Platform

These are some lofty goals, but we think you'll find that Fabric delivers on these promises—oftentimes in ways you may not have ever imagined. This completeness of vision is one of the primary reasons that Microsoft has leapt ahead of the competition in recent years (see Figure 4).

Figure 4: Gartner Magic Quadrant for Analytics & BI Platforms (2024)

Closing Thoughts

As we've seen today, the data landscape is evolving, and while SAP data remains a crucial part of the overall data estate, it's no longer the sole player in the game. These days, there's a lot to think about when it comes to data and the landscape is becoming too big for IT-based data teams to handle on their own.

If you're an SAP customer that's historically been all in on SAP, the thought of hosting SAP data on an data platform like Microsoft Fabric probably sounds like heresy. But, if you've made it this far, then maybe you're willing to come a little bit further. Even if you're skeptical of Fabric itself, I think you'll find value just from looking at some of the various use cases that products like Fabric are designed to address.

So, grab your chessboard and let's delve deeper into the modern SAP data landscape. In my next post, I'll give you the dime tour of Fabric and show you how its unique SaaS model sets it apart from the competition.

Figure 5: Hope for a Consolidated Data Platform is a Good Thing