Empowering your SAP data management strategy with DART—and the right technology
In our previous articles on SAP data management, we touched on the first three principles of the DART methodology—Drivers, Actions, and Requirements. Drivers are pressures (either internal or external) faced by businesses that spur business decisions. Actions are steps taken to address Drivers. Thirdly, Requirements are the processes, people, and capabilities required to undertake successful Actions.
But a fourth and final element is essential to the methodology. In today’s post, I’ll introduce the concept of Technology within the DART framework, along with which technologies businesses have prioritized (or plan to prioritize in the future) for their SAP data management.
The importance of technology within the DART model
SAPinsider’s DART methodology is a fact-based model that distills the connections between the essential elements of an organization’s SAP data management strategy. It identifies company pressures (D), the actions the company takes to deal with those pressures (A), and the resources required to deliver those actions (R).
The Technology element of the DART model (T) represents technologies used by organizations to meet Requirements and, ultimately, to facilitate successful Actions.
It’s important to remember, however, that the DART model is not a prescriptive, one-size-fits-all strategy. Instead, it is a methodology that allows organizations to better understand the forces driving data management, how they’re interconnected, and what steps enterprises are taking with this knowledge. Additionally, organizations in different verticals and with different needs often have different drivers, potential actions, requirements, and preferred technologies, even as many migrate to the SAP S/4HANA next-generation data platform.
Indeed, many organizations still have legacy SAP deployments and data that require different migration and data management approaches:
- Brownfield migrations are “lift-and-shift” deployments (moving entire datasets, applications, and customizations from legacy systems to S/4HANA, for example)
- Greenfield migrations create an entirely new implementation from the ground up, including a new system, configurations, and processes
- Bluefield migrations allow organizations to carefully select which elements to migrate and which ones to rebuild from scratch
Each migration and data management approach requires different technology investments depending on the amount of legacy data and systems involved.
Technology trends related to SAP data management strategy
SAPinsider surveyed nearly 150 global IT professionals in the spring of 2022 to determine, among other things, the most impactful technology trends among organizations navigating the world of SAP data management.
The organization observed that the top data technologies currently used are on-premises databases (51% of respondents), followed by data archiving tools (24%), master data governance (23%), and cloud databases (23%). Around a quarter of respondents indicated they’re rolling out cloud-based extract, transform, load (ETL) tools (26%) and cloud databases (25%).
Respondents indicated they’re planning to implement data integration and orchestration tools (28%), master data governance platforms and tools (25%), cloud-based data warehouses (25%), data management automation (25%), data archiving tools (24%), and data lakes (23%).
Of all data technologies evaluated by organizations, master data governance platforms and tools (28%), data lakes (28%), unstructured data platforms (28%), and data integration and orchestration tools (26%) led the way.
SAPinsider also observed six main SAP analytics solutions currently used for data management and analytics.
SAP BW/4HANA (44%)
BW/4HANA is a next-generation data warehouse that supports smarter data management and analytics. It’s a scalable platform designed to provide more features and capabilities than its predecessor, SAP BW, such as integrating big data sources with SAP operational data sources and integrating various front-end tools.
It’s no surprise that BW/4HANA has captured the most market share of SAP’s data management products since its launch in 2016, as the platform features several improved capabilities. These include simplified administration and data modeling, better user experiences, and the real-time ingestion, storage, and organization of large volumes of data.
SAP Business Warehouse (BW) (41%)
Initially released in 1998 as the Business Warehouse Information System (BIW), SAP BW provided a sea change in how businesses could view and analyze transactional data through daily ingestion, extraction, and transformation, along with built-in reporting and business intelligence (BI) tools. SAP BW on HANA now allows engineers to run data management tasks, such as data tiering (including hot, warm, and cold tiering), archiving, and purging, much faster and more efficiently.
SAP BusinessObjects Business Intelligence (BI) suite (41%)
BusinessObjects Business Intelligence is a suite of BI tools that allow non-technical business users in organizations already on SAP to run their reporting and analytics projects. It can integrate with SAP BW and SAP HANA for real-time analytics and the analysis of massive datasets. It relies on an integrated Data Manager module for moving, mapping, and transforming data.
SAP Analytics Cloud (31%)
SAP Analytics Cloud provides end-to-end data management tools to help facilitate intelligent data preparation, governance, and access. It can integrate with SAP Master Data Governance for real-time data quality monitoring.
SAP Business Planning and Consolidation (BPC) (20%)
SAP BPC has a built-in Data Manager module (mentioned above) integrated with Microsoft Excel that allows users to move, copy, map, and transform data. The module also helps move data into the system across various applications and to export data out of BPC for use with other tools.
SAP Data Warehouse Cloud (13%)
Data Warehouse Cloud combines advanced analytics with data management tools that let users configure, manage, and monitor data within the platform. Data management tools within Data Warehouse Cloud include Data Marketplace, which addresses use cases such as external data integration and data collaboration across the enterprise.
A real-world example of Technology within the DART model
For a real-world Pythian example of how Technology fits into the DART methodology, we only need to look so far as one of the world’s leading footwear manufacturers. The company had dealt with many of the typical Drivers identified in the SAPinsider survey, including IT budget pressures to keep costs under control (31%) and the need to analyze skyrocketing volumes of data (21%).
As these pressures increased, the company realized it needed a trusted partner to implement a more responsive and cost-effective IT infrastructure.
The manufacturer turned to Pythian to migrate its SAP BusinessObjects and SAP BW on an Oracle database to SAP HANA and SAP Adaptive Server Enterprise (ASE) on the cloud. This migration helped it improve reporting performance by 70 percent and significantly reduced IT costs. To learn more about this case study, you can learn more here. For another case study diving into a comprehensive Google Cloud migration featuring advanced analytics and data visualization, click here.
Within this example, we can identify the Action taken as the migration to a more responsive and cost-effective IT environment such as a cloud database or data warehouse (which 30 percent of respondents also identified as a key action in the survey). This Action was accompanied by various Requirements, such as the need to end its relationship with a third-party hosting provider, perform custom code remediation to move it from SAP BW, and restart its SAP maintenance contracts.
To ensure the successful migration to a more responsive IT environment, the company selected SAP HANA and SAP ASE as the Technology element (along with SAP BusinessObjects and SAP BW).
Takeaways: How technology impacts SAP data management strategies
Combining the four elements of DART creates a powerful model that makes it easier to connect the dots between organizational pressures and the strategies and resources (including employees, processes, and technology) needed to combat those pressures.
That said, for organizations currently considering technology options to address data strategy and management, the SAPinsider report provides two main takeaways:
- Have a broad cross-section of employees evaluate technologies: It’s important to include relevant business teams in any technology evaluation process. Organizations that assess new technologies solely through IT teams often encounter unfortunate surprises – and diminished return on investment – after business users get involved.
- Evaluate technologies in a sandbox environment: Set up a sandbox system (an isolated testing environment) so your technical and business users can evaluate data migration, ETL, archiving, and orchestration tools quickly. Assess technologies using an agreed-upon and consistent methodology and metrics.
If you’re searching for a technology implementation and services partner with deep SAP experience, Pythian has a track record of helping global enterprises overcome their toughest data challenges. Our robust partnerships with leading hyperscalers allow us to deliver mission-critical business solutions—from hybrid and cloud migrations to advanced analytics and data visualization. Supported by our diverse teams of analytics, data, and cloud experts, you can expect exceptional guidance and technical expertise that transforms your data management strategy—no matter your requirements.
Comment below if you found this blog helpful – I’d love to hear from you! Please visit our website if you’d like to contact us to learn how we can transform your SAP data strategy. And if you’d like to read the SAPinsider research report in full, you can download it here.