Managing data in large scale SAP transformation

In many of our SAP transformation programs, customers have asked us how to leverage data that has not been migrated to the new SAP S/4HANA platform. During a typical SAP S/4HANA transformation, the primary focus is on designing future business processes or selecting relevant data for day-to-day operations. Usually, any data left behind in the source system is either archived for reference and compliance purposes or decommissioned. As they say, data is the new ‘oil’. We cannot afford to not capitalize on the value of our data while adopting a new implementation or selective data transition approach for transformation. To fully capitalize on the value of data while adopting a new implementation or a selective data transition approach, it is crucial to understand the role of data in the context of the SAP ERP transformation journey. This involves analyzing how to identify data that is relevant for migration to the target SAP S/4HANA system, such as open items and current fiscal year data in the case of a new implementation or a specific range of data for selective organization units or processes. The data can be classified into various categories as part of the transformation process. Data that will move to the future SAP S/4HANA system can be referred to as "business-relevant data" while the remaining data can be segregated for analytics, archiving, or decommissioning purposes. The scope of data relevant to analytics varies from customer to customer. Some customers may require building an equipment dashboard by combining data from the current system and leveraging relevant analytics data. Others may need to report on maintenance history or product batch information for compliance reasons. Additionally, a wider scope of relevant analytics data may be necessary for training AI/ML algorithms to make more accurate predictions. Given customers' varying requirements, it is essential to have a comprehensive solution that addresses the entire data scope within the SAP ERP transformation. The solution should be flexible, allowing customers to select analytics-relevant data according to their specific needs. This data should also undergo the same transformation processes as business-relevant data. Other considerations include minimizing infrastructure costs for managing analytics-relevant data, determining the data format for storage and access via analytics tools, and ensuring the timely transfer of analytics-relevant data from the operational SAP S/4HANA system. Categorizing data in this manner will help organizations leverage their data more effectively, whether they are building a roadmap for transformation or have already initiated or completed the journey.

Our Solution: • Our solution incorporates the Selective Data Transition approach, which ensures that only essential data is captured. Historical data is securely stored in the Azure Data Lake, providing easy access whenever needed. We utilize intelligent reporting tools like Power BI to develop comprehensive reporting and predictive analytics capabilities. Furthermore, we maintain compliance by retaining historical data within the existing ECC model. With our solution, you can efficiently manage data, unlock valuable insights, and easily meet regulatory requirements.
• The solution approach involves identifying relevant business objects for data migration, defining selection criteria, maintaining value mapping, setting up a temporary S/4HANA system for migrating analytical data, and extracting the data to be moved to Azure Data Lake using Azure Data Factory.

Key components: • Azure Data Lake, Azure Data Factory, Azure Connectors, Power BI, and Selective Data Transition Tool. • The Selective Data Transition Tool streamlines the selective data transition process, while Azure Data Lake provides secure storage for non-business-relevant data. • Azure Data Factory creates a data pipeline, and Azure Connectors facilitate data transfer and integration. • Power BI utilizes data from Azure Data Lake and S/4HANA to generate analytics dashboards.

Benefits: Leveraging historical data for day-to-day business activities in the future SAP S/4HANA system brings numerous benefits. It enhances efficiency, improves decision-making by leveraging past insights, and reduces costs by eliminating redundant data storage. Additionally, it enables intelligent processes like trend analysis and predictive analytics, resulting in improved business outcomes and data-driven insights.

Next steps: • Our comprehensive consulting services support customers in assessing, evaluating, and implementing our solutions to achieve their business objectives effectively. Tailored to meet your specific needs, our services include briefing sessions, assessments (approximately 6–8 weeks), PoC projects, workshops, and full-scale implementation based on high-level estimations. We recommend beginning with an assessment and proof-of-concept to ensure a strong foundation.