Data Sync Manager Adoption: Evaluating Template-Based Synchronization for Production Readiness

Authors

  • Sivasankararao Kavuri Data Migration Lead, USA Author

DOI:

https://doi.org/10.15662/IJEETR.2024.0606033

Keywords:

data synchronization, sync manager, template-based synchronization, data sync, production readiness, synchronization templates, data integration, ETL, data pipeline

Abstract

Template-based synchronization tools promise to reduce integration effort by providing pre-built, reusable mapping templates for common data domains, an appealing alternative to custom-coded integration for organizations seeking to reduce build time and long-term maintenance burden. Whether a specific template is actually ready to carry production data reliably, however, is a distinct question from whether it is available and easy to configure, and evaluating that distinction systematically is the subject of this article

This article presents a structured framework for evaluating Data Sync Manager template-based synchronization for production readiness. It defines a multi-dimensional readiness model spanning data quality, performance, error handling, scalability, and maintainability, presents a template evaluation pipeline and pilot program design, and provides a decision framework for adoption. The article is illustrated with a radar chart comparing synchronization approaches, a heatmap of readiness scores by template category, a gauge visualization of overall readiness, a template evaluation funnel, a swimlane process diagram, and a stacked area chart tracking readiness growth across pilot waves, alongside a dense set of reference tables

Illustrative evaluation data presented throughout the article shows template-based synchronization scoring particularly strongly on maintainability and data quality dimensions relative to custom-coded alternatives, while custom-coded approaches retain an advantage in raw performance and scalability, supporting a hybrid adoption strategy for many organizations rather than a uniform choice of one approach over the other.

5 3

References

1. Basili, V. R., Caldiera, G., & Rombach, H. D. (1994). The Goal Question Metric Approach. Encyclopedia of Software Engineering. Wiley.

2. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3).

3. International Organization for Standardization. (2011). ISO/IEC 25040:2011, Systems and Software Quality Requirements and Evaluation (SQuaRE): Evaluation Process. ISO.

4. Kitchenham, B., & Pfleeger, S. L. (1996). Software Quality: The Elusive Target. IEEE Software, 13(1).

5. Moore, G. A. (1991). Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers. Harper Business.

6. Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.

7. SAP SE. (2018). SAP Data Sync Manager: Administrator's Guide. SAP Help Portal.

8. SAP SE. (2019). SAP Business One: Data Transfer Workbench Guide. SAP Help Portal.

9. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3).

10. Zelkowitz, M. V., & Wallace, D. R. (1998). Experimental Models for Validating Technology. IEEE Computer, 31(5).

Downloads

Published

2024-11-11

How to Cite

Data Sync Manager Adoption: Evaluating Template-Based Synchronization for Production Readiness. (2024). International Journal of Engineering & Extended Technologies Research (IJEETR), 6(6), 9338-9356. https://doi.org/10.15662/IJEETR.2024.0606033