With an overwhelming majority of organizations worldwide leveraging SAP products for their enterprise resource planning (ERP), it’s hardly surprising that ERP have started to feel synonymous for organizations looking to upscale their business analytics.
From this entrenched position, a cloud of myths also continues to shroud the possibility of SAP analytics outside its proprietary ecosystem. Many organizations hesitate to explore alternative analytics platforms, primarily due to misconceptions about what options are and aren’t available to them.
In this blog, we delve into these myths and shed light on why breaking free from the SAP bubble is not as daunting as it may seem.
Myth: SAP Workloads are Too Complex to Export
One of the most pervasive myths is the notion that SAP business analytics are simply too complex to function effectively outside of the SAP ecosystem. Organizations fear that transitioning their analytics workloads to other platforms would be overly complicated and fraught with risk.
However, this belief is more speculative than fact. SAP is not an impenetrable fortress of complexity. SAP’s structure, though comprehensive, is well-organized and accessible with the right expertise. With a sound strategy and knowledgeable personnel, businesses can easily navigate the perceived complexities and leverage SAP data in external analytics platforms. Furthermore, the sophisticated analytics capabilities of platforms like the Snowflake AI Data Cloud mean that there are often considerable cost and efficiency benefits to doing so. The key lies in decoupling the various processes operating under the hood of your SAP environment and ultimately recognizing that SAP itself is not a monolithic black box but a flexible tool that can be integrated with diverse systems.
Myth: SAP is Difficult to Integrate with Other Sources
Contrary to popular belief, SAP is not an isolated system that resists external data integration. On the contrary, it is one of the most meticulously documented (and therefore integration-friendly) systems on the market — provided you approach it with the right strategy and expertise.
SAP’s metadata-driven design plays a crucial role in its integration capabilities. Metadata provides detailed descriptions of data structures, making it easier to understand and manipulate data within and outside the SAP ecosystem. This structure ensures that data is not trapped within an opaque system but is readily accessible for various analytical purposes.
Established methods and tools exist to facilitate data exports and imports, streamlining the integration process. At its simplest, SAP even offers numerous APIs, connectors, and middleware options that enable data to flow between SAP systems and other platforms. This interoperability allows organizations to leverage a variety of analytics tools, ensuring that their data strategies are both versatile and comprehensive.
Ultimately, understanding SAP’s integration potential can empower organizations to expand their analytics horizons. By leveraging well-documented integration methods, coupled with support from a data partner like Hakkoda, businesses can combine the strengths of SAP with other analytics platforms, maximizing their data’s value and enhancing their strategic decision-making capabilities.
Myth: SAP’s Analytics Platform is the Low Risk Option
The assumption that SAP data modeling is somehow fundamentally different from data engineering practices in modern platforms like Snowflake is inherently flawed. In practice, the processes involved in managing BW content are remarkably similar to those employed in cloud-based data solutions. The critical factor is not the proprietary nature of SAP but the functional expertise of the professionals handling the data.
The skills necessary for managing BW content — such as understanding data structures, ETL processes, and data governance — are transferable to other modern analytics platforms. Professionals well-versed in SAP BW can easily adapt their expertise to manage and integrate data in platforms like Snowflake. This adaptability underscores that there is no secret sauce exclusive to SAP. Rather, it’s about applying robust data management practices universally.
Knowing how data is generated, what business processes it supports, and how it can be used for insights are pivotal aspects of data management, regardless of the platform. This knowledge allows professionals to ask the right questions and address potential issues effectively, ensuring the integrity and utility of the data.
In essence, the real value lies in the expertise of the individuals managing the data, not in the exclusivity of the SAP analytics tools. By recognizing this, organizations can confidently explore alternative platforms for their analytics needs, maximizing their analytics budget’s ROI and reach of their data.
Time for a Second Opinion: Breaking Away from the SAP Ecosystem with Hakkōda
Global Systems Integrators (GSIs) significantly influence how organizations perceive and adopt SAP solutions. These entities are often incentivized by SAP to prioritize its analytics offerings, leading to a predominant focus on SAP-centric solutions and a reinforcement of many of the myths surrounding the SAP proprietary ecosystem. Another unfortunate side effect of this influence is the ongoing prevalence of “Swivel Chair” strategies in the SAP migration space.
Put simply, GSIs have a vested interest in maintaining strong partnerships with SAP and often receive financial incentives and technical support for promoting SAP products. This arrangement can skew the guidance provided to organizations, reinforcing the myth that SAP solutions are the only viable option for ERP analytics workloads.
However, this SAP-centric focus does not always align with the diverse and evolving needs of modern businesses. Other analytics platforms, such as Snowflake, offer robust capabilities that surpass SAP’s offerings in certain scenarios. These platforms often provide enhanced security, flexibility, scalability, and integration features that can better support an organization’s unique data strategy while saving them on maintenance and compute costs.
By seeking independent advice and exploring a variety of solutions, companies can develop a more holistic and effective analytics strategy. Unifying multiple data sources with the help of a platform like Snowflake often provides enterprises a richer, more nuanced understanding of their business operations, which in turn drives better decision-making and a steeper competitive advantage.
Ready to see how breaking away from SAP for your analytics workloads can help your organization slash costs and synthesize a more holistic view of your enterprise? Let’s talk today.
