A data pipeline is a crucial tool for businesses, helping them collect, organize and use information from various internal and external sources. It involves aggregating data, storing it and transforming it so that analysts can understand it. The six key components of building a data pipeline include data sources, collection, processing, destinations, workflow, and monitoring. There are two main types of data pipeline architectures: ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). Technical considerations for data pipeline architecture include automation, performance, reliability, scalability, and security.