Designing a Data Integration Pipeline

Integrating data from various sources into a software system efficiently and reliably remains a complex challenge for many businesses. Despite advancements in standardized data formats and APIs, a significant portion of IT decision-makers find onboarding new business data overly complex and resource-intensive. Establishing a data integration pipeline involves accepting data from multiple sources, handling diverse formats, and ensuring data integrity throughout the process. To address these challenges, a four-phase pipeline architecture is suggested, leveraging AWS services such as Lambda, SQS, and API Gateway to create a cost-effective, scalable solution. The process involves receiving data through an API, parsing and validating it into a standard format, transforming the data based on customer-specific logic, and finally executing transactions via a standard API. The system is designed to be flexible, using interchangeable parts and adhering to the Single Responsibility Principle to simplify development and maintenance. The infrastructure is set up using serverless technologies to manage costs and scalability, with additional environments for testing and production managed through Nullstone, providing a streamlined approach to deploying and modifying the pipeline as needed.