A data pipeline is a systematic process that transports data from a source to a destination, often aiding decision-making or enhancing AI capabilities. Effective data pipeline architecture can streamline business processes by consolidating data from various sources, reducing friction, ensuring data uniformity, and maintaining data compartmentalization for relevant stakeholders. Big data pipelines are designed to manage data collection, processing, and implementation at scale, supporting applications like predictive analytics and real-time market capture. There are different types of data pipeline architectures, such as streaming, batch-based, and hybrid, each suited to different business needs, with the choice between them being crucial for a company's success. Unlike ETL pipelines, which focus on data warehousing and integration, data pipelines ensure the systemic functioning of data collection, formatting, and transfer processes.