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What is Data Modeling Strategy

Chapter 6
The Software Principles of Design for Data Modeling
The approach or plan for creating a data model that meets the requirements of the application being developed. A data modeling strategy should consider the characteristics of the data, the business rules governing the data, and the constraints of the technology and architecture being used. In the context of microservices, a data modeling strategy should consider the need for data consistency across services, the impact of service boundaries on data access, and the trade-offs between data duplication and data sharing.
Published in Chapter:
The Art of Breaking Down: Mastering Microservice Architecture and Data Modeling Strategy
Tapan Kumar Behera (Department of Technology Management, Forrester Research, USA)
Copyright: © 2023 |Pages: 16
DOI: 10.4018/978-1-6684-9809-5.ch006
Abstract
Microservice architecture (MSA) is a popular software architecture style for developing scalable and resilient applications. However, designing data models for MSA presents unique challenges that require careful consideration. This chapter explores the relationship between MSA and data modeling and provides insights into best practices for designing data models that are optimized for MSA. It defines MSA and its key principles, examines the implications of MSA on data modeling, and discusses strategies for designing data models that are modular, decoupled, and flexible. The chapter also presents several case studies of organizations that have implemented MSA and data modeling strategies and discusses future trends in MSA and data modeling strategy, including the use of artificial intelligence and machine learning to automate data modeling. By following the best practices outlined in this chapter, organizations can realize the benefits of MSA while ensuring data consistency, scalability, and maintainability.
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