Data pipeline architecture refers to the integration of various components involved in gathering, processing, transporting, and storing data. A basic data pipeline will have data sources, data ingestion layer, processing/transformation system, data storage, and ultimately, the end-point for analysis. Data will first go through application/database, be transformed into usable information, then eventually stored in a data warehouse. Some of the best architectures are designed with scalability, reliability, security, and ease of monitoring in mind. There are different types of architectures that may be selected based on whether the business requires batch processing or real-time processing or both. Some of the available tools in the market can be applied during different phases to manage data extraction, transformation, orchestration, and monitoring. Data pipeline architectures are also important in enabling the automation of data pipeline since recurring tasks can easily be scheduled.