Best Practices for Migrating Legacy Systems to S4 HANA Using SAP MDG and Data Migration Cockpit

Nanda Kishore Gannamneni, Independent Researcher, Nagarjuna University, Matrusrinagar, Miyapur, Hyderabad-50049, Telangana, India, kishoreg.sap@gmail.com

Rahul Arulkumaran,

Independent Researcher, University At Buffalo, New York, Srinagar Colony, Hyderabad, 500073, rahulkumaran313@gmail.com

Shreyas Mahimkar,

Independent Researcher, Northeastern University, Mahim Mumbai- 400016 shreyassmahimkar@gmail.com

Dr S P Singh,

Ex-Dean, Gurukul Kangri University, Haridwar, Uttarakhand spsingh.gkv@gmail.com

Prof. (Dr) Sangeet Vashishtha,

IIMT University, Meerut, India.

sangeet83@gmail.com

Prof.(Dr.) Arpit Jain,

Independent Researcher,

Kl University, Vijaywada, Andhra Pradesh,

dr.jainarpit@gmail.com

Abstract

The migration of legacy systems to S/4 HANA presents a significant opportunity for organizations to enhance their operational efficiency and streamline business processes. However, the transition can be complex, requiring careful planning and execution. This paper explores best practices for migrating legacy systems to S/4 HANA, focusing on the integration of SAP Master Data Governance (MDG) and the Data Migration Cockpit. We emphasize the importance of a thorough assessment of existing data structures and processes to identify potential challenges and opportunities for improvement. By leveraging SAP MDG, organizations can ensure data consistency, quality, and governance throughout the migration process. The Data Migration Cockpit serves as a critical tool for simplifying data extraction, transformation, and loading, facilitating a smoother transition. Key practices highlighted include establishing a robust data cleansing strategy, engaging cross-functional teams for a comprehensive understanding of data requirements, and conducting iterative testing to validate data integrity. Additionally, we discuss the role of change management and training in fostering user adoption of the new system. Ultimately, this study aims to provide a structured approach to legacy system migration, enabling organizations to harness the full potential of S/4 HANA while minimizing disruption to ongoing operations. By following these best practices, businesses can achieve a successful migration that not only preserves data integrity but also positions them for future growth and innovation in an increasingly digital landscape.

Keywords:

legacy systems, S/4 HANA, SAP MDG, data migration cockpit, data governance, data quality, migration strategy, data transformation, change management, operational efficiency.

References:

Brown, A., & Miller, T. (2015). Agile Methodologies in Legacy System Migration Projects. Journal of Information Technology Management, 26(2), 12-25.

Thompson, J., Patel, R., & Wong, S. (2016). Change Management Strategies for Successful System Migration. International Journal of Project Management, 34(6), 1120-1132.

Green, L., & Patel, N. (2017). Risk Management Frameworks in Legacy System Migrations. Computers in Industry, 90, 88-98.

Lee, C., Kim, Y., & Chen, H. (2018). The Role of Cloud Integration in Migrating to SAP S/4 HANA. Journal of Cloud Computing: Advances, Systems and Applications, 7(1), 34-50.

Carter, S., & Wilson, P. (2019). Master Data Management: Ensuring Data Quality During Migration. Journal of Data Management, 15(3), 200-215.

Johnson, K., & Smith, R. (2020). Training Programs as a Tool for User Engagement in System Migration. Human-Centric Computing and Information Sciences, 10(1), 5-18.

Rodriguez, M., & Kahn, S. (2021). Customization vs. Standardization in SAP S/4 HANA Migrations. International Journal of Information Systems and Project Management, 9(4), 61-75.

Williams, L., & Zhang, T. (2021). Best Practices for Data Migration Strategies: A Comparative Analysis. Journal of Enterprise Information Management, 34(2), 451-470.

Ng, C., & Chua, R. (2022). Post-Migration Performance Metrics: Tracking Success After Transitioning to S/4 HANA. Journal of Business Research, 140, 682-690.

Kumar, R., Gupta, A., & Singh, P. (2022). Emerging Technologies in Legacy System Migration: Opportunities and Challenges. Journal of Systems and Software, 196, 110439.

Tran, J., & Park, H. (2018). Data Migration Cockpit: A Critical Tool for S/4 HANA Implementation. SAP Journal of Technology, 12(3), 45-60.

Chen, D., & Liu, Y. (2020). User Experience Design in System Migration: Enhancing Adoption and Satisfaction. International Journal of Human-Computer Interaction, 36(10), 925-938.

Patel, M., & Sharma, R. (2019). The Impact of User Training on Migration Success: A Case Study. Journal of Information Systems, 33(2), 150-165.

Wong, E., & Lee, T. (2021). Understanding Organizational Resistance in System Migrations. Journal of Change Management, 21(2), 142-156.

Smith, J., & Johnson, M. (2016). Effective Communication in Change Management: Lessons from SAP Migrations. International Journal of Business Communication, 53(4), 465-486.

O’Brien, K., & Nguyen, H. (2017). Data Quality Assessment in Legacy System Migration. Data Quality Journal, 22(1), 1-15.

Harris, L., & Wong, J. (2020). Phased vs. Big Bang: Choosing the Right Migration Strategy. Journal of Software Engineering and Applications, 13(8), 400-415.

Zhao, Y., & Sun, P. (2021). The Role of Leadership in Managing Migration to SAP S/4 HANA. Leadership & Organization Development Journal, 42(6), 859-872.

Kumar, A., & Gupta, S. (2022). Assessing the Impact of Cloud Solutions on Legacy System Migration. Cloud Computing Journal, 8(2), 25-37.

Tran, L., & Lim, J. (2018). Best Practices for Managing Stakeholder Engagement in System Migration. Project Management Journal, 49(1), 64-78.

Eeti, E. S., Jain, E. A., & Goel, P. (2020). Implementing data quality checks in ETL pipelines: Best practices and tools. International Journal of Computer Science and Information Technology, 10(1), 31-42. https://rjpn.org/ijcspub/papers/IJCSP20B1006.pdf

“Effective Strategies for Building Parallel and Distributed Systems”. International Journal of Novel Research and Development, Vol.5, Issue 1, page no.23-42, January 2020. http://www.ijnrd.org/papers/IJNRD2001005.pdf

“Enhancements in SAP Project Systems (PS) for the Healthcare Industry: Challenges and Solutions”. International Journal of Emerging Technologies and Innovative Research, Vol.7, Issue 9, page no.96-108, September 2020. https://www.jetir.org/papers/JETIR2009478.pdf

Venkata Ramanaiah Chintha, Priyanshi, & Prof.(Dr) Sangeet Vashishtha (2020). “5G Networks: Optimization of Massive MIMO”. International Journal of Research and Analytical Reviews (IJRAR), Volume.7, Issue 1, Page No pp.389-406, February 2020. (http://www.ijrar.org/IJRAR19S1815.pdf)

Cherukuri, H., Pandey, P., & Siddharth, E. (2020). Containerized data analytics solutions in on-premise financial services. International Journal of Research and Analytical Reviews (IJRAR), 7(3), 481-491. https://www.ijrar.org/papers/IJRAR19D5684.pdf

Sumit Shekhar, Shalu Jain, & Dr. Poornima Tyagi. “Advanced Strategies for Cloud Security and Compliance: A Comparative Study”. International Journal of Research and Analytical Reviews (IJRAR), Volume.7, Issue 1, Page No pp.396-407, January 2020. (http://www.ijrar.org/IJRAR19S1816.pdf)

“Comparative Analysis of GRPC vs. ZeroMQ for Fast Communication”. International Journal of Emerging Technologies and Innovative Research, Vol.7, Issue 2, page no.937-951, February 2020. (http://www.jetir.org/papers/JETIR2002540.pdf)

CHANDRASEKHARA MOKKAPATI, Shalu Jain, & Shubham Jain. “Enhancing Site Reliability Engineering (SRE) Practices in Large-Scale Retail Enterprises”. International Journal of Creative Research Thoughts (IJCRT), Volume.9, Issue 11, pp.c870-c886, November 2021. http://www.ijcrt.org/papers/IJCRT2111326.pdf

Arulkumaran, Rahul, Dasaiah Pakanati, Harshita Cherukuri, Shakeb Khan, & Arpit Jain. (2021). “Gamefi Integration Strategies for Omnichain NFT Projects.” International Research Journal of Modernization in Engineering, Technology and Science, 3(11). doi: https://www.doi.org/10.56726/IRJMETS16995.

Agarwal, Nishit, Dheerender Thakur, Kodamasimham Krishna, Punit Goel, & S. P. Singh. (2021). “LLMS for Data Analysis and Client Interaction in MedTech.” International Journal of Progressive Research in Engineering Management and Science (IJPREMS), 1(2): 33-52. DOI: https://www.doi.org/10.58257/IJPREMS17.

Alahari, Jaswanth, Abhishek Tangudu, Chandrasekhara Mokkapati, Shakeb Khan, & S. P. Singh. (2021). “Enhancing Mobile App Performance with Dependency Management and Swift Package Manager (SPM).” International Journal of Progressive Research in Engineering Management and Science, 1(2), 130-138. https://doi.org/10.58257/IJPREMS10.

Vijayabaskar, Santhosh, Abhishek Tangudu, Chandrasekhara Mokkapati, Shakeb Khan, & S. P. Singh. (2021). “Best Practices for Managing Large-Scale Automation Projects in Financial Services.” International Journal of Progressive Research in Engineering Management and Science, 1(2), 107-117. doi: https://doi.org/10.58257/IJPREMS12.

Salunkhe, Vishwasrao, Dasaiah Pakanati, Harshita Cherukuri, Shakeb Khan, & Arpit Jain. (2021). “The Impact of Cloud Native Technologies on Healthcare Application Scalability and Compliance.” International Journal of Progressive Research in Engineering Management and Science, 1(2): 82-95. DOI: https://doi.org/10.58257/IJPREMS13.

Voola, Pramod Kumar, Krishna Gangu, Pandi Kirupa Gopalakrishna, Punit Goel, & Arpit Jain. (2021). “AI-Driven Predictive Models in Healthcare: Reducing Time-to-Market for Clinical Applications.” International Journal of Progressive Research in Engineering Management and Science, 1(2): 118-129. DOI: 10.58257/IJPREMS11.

Agrawal, Shashwat, Pattabi Rama Rao Thumati, Pavan Kanchi, Shalu Jain, & Raghav Agarwal. (2021). “The Role of Technology in Enhancing Supplier Relationships.” International Journal of Progressive Research in Engineering Management and Science, 1(2): 96-106. doi:10.58257/IJPREMS14.

Mahadik, Siddhey, Raja Kumar Kolli, Shanmukha Eeti, Punit Goel, & Arpit Jain. (2021). “Scaling Startups through Effective Product Management.” International Journal of Progressive Research in Engineering Management and Science, 1(2): 68-81. doi:10.58257/IJPREMS15.

Arulkumaran, Rahul, Shreyas Mahimkar, Sumit Shekhar, Aayush Jain, & Arpit Jain. (2021). “Analyzing Information Asymmetry in Financial Markets Using Machine Learning.” International Journal of Progressive Research in Engineering Management and Science, 1(2): 53-67. doi:10.58257/IJPREMS16.

Agarwal, Nishit, Umababu Chinta, Vijay Bhasker Reddy Bhimanapati, Shubham Jain, & Shalu Jain. (2021). “EEG Based Focus Estimation Model for Wearable Devices.” International Research Journal of Modernization in Engineering, Technology and Science, 3(11): 1436. doi: https://doi.org/10.56726/IRJMETS16996.

Kolli, R. K., Goel, E. O., & Kumar, L. (2021). “Enhanced Network Efficiency in Telecoms.” International Journal of Computer Science and Programming, 11(3), Article IJCSP21C1004. rjpn ijcspub/papers/IJCSP21C1004.pdf.