The scheduled end-of-life of SAP BW (2027 or latest 2030) and SAP BW/4HANA is a strong incentive for many companies to consider migrating to a modern data platform. Although SAP has extended maintenance, it's key to understand that innovation and major investments are now focused on newer solutions such as SAP Business Data Cloud, Databricks and Microsoft Fabric. Eventually, companies will be forced to decommission their SAP BW systems to remain competitive, benefit from the latest technological breakthroughs and ensure the longevity of their analytical infrastructures. Anticipating this transition and planning a gradual journey to a more modern platform is therefore an essential strategic move to avoid greater costs and disruption in the future.
element61 is a trusted partner that supports many companies on their modernization path and their data platforms. This article provides an insight into the fundamental reasons behind such a modernization (why), the crucial steps involved in the process (how) and, finally, the tools we provide to make the transformation a success (what).
Why should companies evolve beyond legacy systems
Understanding the underlying reasons for modernizing data platforms is of prime importance, as it represents a strategic necessity for companies. The need to migrate SAP BW systems is rooted in a combination of factors that are critical to the future of enterprise data analytics.
The rise of modern (cloud-based) data platforms has transformed how businesses manage and leverage data, offering greater scalability, flexibility, and cost efficiency. These platforms natively integrate Al and machine learning, enabling advanced predictive and prescriptive analytics that traditional architectures struggle to support. The expansion of self-service BI and the democratization of data have accelerated this transition, pushing companies to move away from SAP BW towards more agile solutions. Business users now expect to generate insights independently, without relying on IT teams or data specialists, enhancing agility and decision-making speed.
While SAP BW remains powerful, its rigid data structures require advanced technical expertise, limiting user autonomy. New platforms like Microsoft Fabric, Databricks, and SAP Datasphere empower users with direct access to data, allowing them to build interactive visualizations and extract insights seamlessly. This shift fosters collaboration and innovation, enabling users to experiment and refine their analytics in real time. Integrated BI tools eliminate batch processing needs, delivering instant business performance insights.
Although SAP BW can be extended until 2030 and SAP BW/4HANA will be maintained until 2040, companies should recognize that out of support dates are coming & inevitably marks the end of its strategic lifecycle. SAP's future innovation and investments are now focused on more modern data platforms, designed to meet the challenges and opportunities of the digital age. Sticking to BW for too long could therefore slow down the adoption of advanced analytical capabilities and render the data infrastructure progressively obsolete.
Image credits to Dr. Mahesh Kumar as posted on LinkedIn
What's more, the Lakehouse concept is growing fast. It combines the advantages of data lakes (low-cost storage of raw, varied data) and data warehouses (structuring and governance for analysis). Modern platforms make it possible to build Lakehouse-type architectures, offering a unified view of data, facilitating exploration, data science and reporting, while ensuring the necessary quality and governance. Migrating to such an architecture enables companies to make the most of all their information assets.
How to plan this modernization from SAP BW
Migrating from SAP BW to a modern data platform is a significant transformation that goes beyond just switching technologies, it requires a well-structured modernization plan. Whether you're moving to SAP Datasphere, Databricks, or Microsoft Fabric, success depends on following clearly defined steps, supported by a solid roadmap, targeted proof of concepts, and the right migration strategy. Breaking the process into manageable phases and applying change management frameworks like ADKAR helps reduce risk. Just as importantly, involving end users early ensures the solution meets business needs and gains broader adoption.
Step 1 - Kickstart with an analytics roadmap
A well-defined, future-proof, roadmap is key when migrating from legacy BW to a modern data platform because it aligns technical execution with business strategy. First, it ensures clarity on future ambitions, helping organizations define key objectives and success metrics for the new platform. To do so, we start from an as-is situation to determine the best direction for the coming years, taking into account: data architecture, data visualization, SaaS solutions and user adoption strategy.
The selection of an appropriate modern data platform is determined based on the organization's specific requirements and scope. Each platform offers distinct capabilities that must be carefully evaluated to align with business objectives:
We will explore these three platforms in greater depth in an upcoming blog, where we'll dive into their unique capabilities and how to leverage them for a seamless migration. Ultimately, assess the required resources and expertise to determine whether external consultants with SAP-to-cloud migration experience are necessary.
The roadmap is a key element to minimize risk, by identifying dependencies, challenges and required resources, making the transition smoother and more predictable. Next, it is a way to foster stakeholder buy-in and collaboration, ensuring all teams are aligned during the migration process.
Step 2 - Do a Proof of Concept
The Proof of Concept (POC) is a core step in validating the feasibility and effectiveness of migrating from SAP BW to a new platform. This also allows the different stakeholders to become familiar with the new environment and tools and tends to be a smooth transition to what comes next. The PoC phase begins with the selection of 2 to 3 representative reports, covering different levels of complexity. These reports are then recreated as prototypes in the target solution, being SAP BDC, Microsoft Fabric, or Databricks. During development, it is crucial to document connectivity methods used for data extraction and transformation while identifying technical challenges related to integration. Special attention is given to data accuracy validation, comparing outputs from the new platform against SAP BW results to ensure full consistency. This process helps identify potential gaps, refine migration strategies, and optimize performance before full-scale implementation.
A successful PoC will help stakeholders move forward with the project, prove to product teams and users that the set-up makes sense in bring them confidence for further implementation.
Step 3 - Define your Modernization Strategy
When planning a data warehouse migration, it's important to balance speed, cost, technical complexity, and long-term value.
There's no one-size-fits-all approach, each organization must choose the path that aligns with its goals, resources, and desire for change. Below are three common strategies we typically propose, each with its own trade-offs in terms of effort, risk, and future flexibility.
- Lift & Shift: This approach involves moving the existing data model and pipelines to the new platform without making major changes. Business logic and structure remain the same. It requires minimal involvement from business teams and can be executed in the background. However, technical debt is carried over, and refactoring is typically needed after the migration. It's often seen as an IT-driven project with limited immediate business value.
- Build on the Side (Greenfield): In this option, we start fresh by redesigning the data model and ETL processes from scratch. The existing data warehouse is not used as a source. This eliminates legacy issues and allows for modern, streamlined architecture. However, it requires significant time and effort, including reconnecting to all data sources and rebuilding business logic. For a period, both the old and new platforms must run in parallel, increasing the operational load and requiring dual skillsets.
- Build on Top: Here, the new platform is built by using the existing data warehouse as a source. We redesign the data model where possible, but we don't start from scratch. This reduces the need to redo everything and avoids a full lift-and-shift followed by heavy refactoring. However, it introduces a dependency on the legacy system for certain data and logic. While some modernization is achieved, not all legacy risks are eliminated, and parallel operations are still required during the transition.
Regardless of the chosen migration path, successful data warehouse migration requires tight alignment between project management and scope management. A clear and realistic scope helps avoid surprises during execution and ensures all stakeholders share the same expectations. Migration projects often span both technical and business domains, so project management must bridge IT and business priorities, balancing delivery speed with data quality and governance. Scope should be broken down into manageable, value-driven phases, whether by layer, use case, or domain, to allow for incremental delivery and reduce risk. It's also important to account for dependencies on existing systems, business validation cycles, and the dual-run phase, where old and new platforms operate in parallel.
Step 4 - Slice the elephant in pieces
Migrating from SAP BW to a modern platform requires a structured approach to safeguard data integrity, performance, and business continuity. This process begins with an initial assessment, where the existing data landscape is meticulously documented. This includes cataloging InfoProviders, data models, SAP BW queries, and key performance indicators (KPIs) by domain. A thorough review of ETL processes helps map data flows across the system, ensuring smooth transition. Organizations must also evaluate custom ABAP code embedded in transformations, assessing its compatibility and determining the extent to which it can be migrated. The assessment phase often involves mapping SAP BW objects to their counterparts in the target system, such as fact tables, dimensions, or data lakes.
To streamline migration, objects are classified by complexity (simple, medium, or complex) while reports are categorized based on their business criticality, allowing for a phased and strategic migration. This prioritization ensures essential processes remain uninterrupted while optimizing data structures for the new environment.
We typically adopt a phased approach to DWH migrations. A phased approach to SAP BW migration is highly recommended to minimize business disruption and ensure a successful transition.
- Bottom-up: One option is a bottom-up strategy, where we migrate layer by layer, starting with the extraction layer, then transformations, and finally loads. While this method minimizes disruption to business teams, we've found it often fails to deliver timely results and can lose momentum due to the delayed visibility of business value.
- Use-case driven: Another approach is use-case driven, where we start with a high-priority business use case and build it end-to-end on the new platform. This ensures tangible business outcomes early in the process but can lead to a fragmented migration, as the underlying structure is not systematically modernized.
- Domain-driven: Lastly, a domain-driven approach strikes a balance by addressing a strategic business use case within a broader domain, allowing us to deliver meaningful results while also modernizing a larger part of the landscape. This helps reduce legacy dependencies and breaks the migration effort into manageable phases. For each domain, we suggest following a structured sequence: first, the transfer of historical data loads, incremental updates and real-time streaming. The transformation logic embedded in SAP BW will need to be re-engineered using SQL-based transformation. Finally, the reporting layer is migrated, meaning reports are rebuilt in Power BI or SAP Analytics cloud. By applying a domain-based approach, organizations can put the focus on critical business areas first.
After each phase, validation procedures should be conducted to confirm data integrity. During the transition, parallel system operations enable continuous data comparisons and reconciliation tracking. Once all complexities or domains are addressed, a structured transition plan should be implemented, including a cutover strategy, training programs, and final validation, ensuring seamless migration and effective system decommissioning.
Step 5 - Involve everyone & don't skip an ADKAR step
The migration from BW to a modern data platform goes beyond a technical migration. It is important that organizations become ready to work in this new set-up and that's why it is of prime importance to invest in change and put effort into change management. Indeed, a good change management plan transforms the technological transition into an opportunity for the company.
At element61, we apply the ADKAR framework to provide a structured approach to change management and ensure alignment and engagement throughout the whole migration process. The idea is to facilitate adoption by minimizing disruption and maximizing the benefits of the new system. Good change management helps to communicate the vision, explain the benefits and involve the employees concerned from the outset, thereby reducing resistance to change. Change management must also ensure that teams receive the appropriate training and resources to facilitate adoption. But, it must not stop after technical migration. Post-migration support is the key to successful adoption.
Creating awareness is key in helping stakeholders understand why the change is necessary and how it will impact them. Awareness can be fostered by hosting webinars, running inspiration sessions and building a communication plan. By creating Awareness, we aim to create a strong Desire for change. Once awareness and desire are established, the Knowledge phase ensures that users are equipped with the right skills to go through the transition. element61 Academy proposes training plans, designed to fit different personas, including a mix of self- study resources, structured trainings, and coaching sessions. Our goal is to ensure that all users, regardless of their level of expertise, feel confident in adopting the new tools. For the Ability and Reinforcement stages, we share responsibilities with the client organization. It's important to ensure that users can confidently apply their new knowledge in practice. Support structures such as community events and expert sessions help foster collaboration, allowing employees to share insights and troubleshoot challenges. Encouraging participation in peer-led discussions and ongoing development programs reinforces adoption, ensuring that the transition is not only successful but sustainable in the long term.
Step 6 - Involve end-users early-on
Finally, one of the major challenges of the transition is getting users on board. By giving them simple, powerful tools to explore data on their own, companies can make migration smoother and encourage greater commitment from business teams. Self-service makes modern platforms much more accessible and efficient, while improving collaboration between IT and business. With a self-service approach, users can access, explore and analyze data, and no longer have to systematically go through technical teams. Self-service seems to be a real added value of modern platforms.
How do we accelerate your move beyond SAP BW
At element61, we have a unique asset to accelerate and simplify the migration process for companies: i.e. our "Out-of-the-Box" acceleration solutions combined with our elementary project approach. To accelerate we thus bring a methodology based on our experience and practices, as well as pre-configured tools.
What is our Out-of-the-Box
Specifically, we have designed kits containing scripts, templates, connectors and pre-built workflows, to automate certain migration tasks, notably data extraction, loading and transformation. The solution is of course customizable to the specific needs of each company. In addition, element61 has a team of consultants experienced in SAP BW and cloud platforms.
Our Out-of-the-Box solution is built on five key pillars:
- Accelerate: Speed up insights across 10+ functional domains with pre-packaged BI components, using proven frameworks, efficient data ingestion, and a pre-defined data model to save time and focus on business-specific needs.
- One Data Model: Unify multiple data sources into a consistent, single source of truth, simplifying data management and enhancing accuracy.
- Self-service: Empower users with pre-configured, customizable dashboards and models, enabling independent data access and visualization without IT reliance.
- Continuity while Migrating: Maintain consistent analytics when transitioning between ERP systems by mapping changes in master data, ensuring seamless historical and future reporting.
- Industry Experience: Leverage best-practice analytics and tailored KPIs across industries like Food, Retail, Construction, Manufacturing, and more, enabling faster and more effective Bl implementations.
Such a solution represents an effective, low-risk way for any company wishing to migrate its on-premise environment. It considerably reduces implementation times and costs, and as a result, accelerates data enhancement, enabling companies to benefit more quickly from advanced analytical capabilities.
Interested to continue reading
Stay tuned...! Get ready to dive deep into the future of your SAP BW environment. In this series of articles, we'll uncover the cutting-edge data ingestion tools designed to push your SAP data towards modern platforms. Next to this, we will explore the strengths and unique features of leading market solutions like SAP Business Data Cloud, Microsoft Fabric, and Databricks. Plus, we'll guide you through key migration strategies to ensure seamless business continuity when transitioning from SAP ECC to S/4HANA, all brought to life with an inspiring success story from one of our past projects.
More information
This blog is part of a blog series about how companies can modernise their current SAP BW landscape by bringing it to the cloud.
- Modernising SAP BW Blog Series Part 1: From legacy to innovation: steps to migrate from SAP BW to a Modern Data Platform
- Modernizing SAP BW Blog Series Part 2: Unlocking SAP Data: overcoming challenges in Modern Data integration
- Modernising SAP BW Blog Series Part 3: Beyond BW: Building a scalable modernisation strategy with SAP Business Data Cloud
In this article & our previous articles, we have already outlined a solid base. However, details matter, and you want to ask an expert advice on how to modernise your legacy BW system? Don't hesitate to reach out via info@element61.be. Let's shape the future of your data strategy together. We have some SAP BW experts ready to help and guide you further!
