Transformation patterns
Data transformation has given rise to several different architectural patterns for more effective data management, processing, and storage. These patterns offer a roadmap for developing software that can cope with the growing volume, velocity, and variety of data. The Lambda, Kappa, and Microservice architectures will be discussed in this section as they are all examples of common transformation patterns.
Choosing the correct transformation pattern is crucial if a business is to maximize the value of its data and data assets. Different situations call for the use of different design patterns due to their strengths and weaknesses.
When deciding between different transformation patterns, it’s important to think about things such as scalability, flexibility, maintainability, and fault tolerance. Consider your organization’s specific requirements and constraints, such as its available funds, personnel, and technology.
In the following sections...
