"A series of operations in an aggregation process." (MongoDb, "Glossary", 2008)
"A series of processes all in a row, linked by pipes, where each passes its output stream to the next." (Jon Orwant et al, "Programming Perl" 4th Ed., 2012)
"Description of the process workflow in sequential order." (Hamid R Arabnia et al, "Application of Big Data for National Security", 2015)
"In data processing, a pipeline is a sequence of processing steps combined into a single object. In Spark MLlib, a pipeline is a sequence of stages. A Pipeline is an estimator containing transformers, estimators, and evaluators. When it is trained, it produces a PipelineModel containing transformers, models, and evaluators." (Alex Thomas, "Natural Language Processing with Spark NLP", 2020)
"Abstract concept used to describe where work is broken into several steps which enable multiple tasks to be in progress at the same time. Pipelining is applied in processors to increase processing of machine language instructions and is also a category of functional decomposition that reduces the synchronization cost while maintaining many of the benefits of concurrent execution." (Max Domeika, "Software Development for Embedded Multi-core Systems", 2011)
"A technique that breaks an instruction into smaller steps that can be overlapped" (Nell Dale & John Lewis, "Computer Science Illuminated" 6th Ed., 2015)
[pipeline pattern:] "A set of data processing elements connected in series, generally so that the output of one element is the input of the next one. The elements of a pipeline are often executed concurrently. Describing many algorithms, including many signal processing problems, as pipelines is generally quite natural and lends itself to parallel execution. However, in order to scale beyond the number of pipeline stages, it is necessary to exploit parallelism within a single pipeline stage." (Michael McCool et al, "Structured Parallel Programming", 2012)
"A data pipeline is a general term for a process that moves data from a source to a destination. ETL (extract, transform, and load) uses a data pipeline to move the data it extracts from a source to the destination, where it loads the data." (Jake Stein)
"A data pipeline is a piece of infrastructure responsible for routing data from where it is to where it needs to go and provide any necessary transformations through that process." (Precisely) [source]
"A data pipeline is a service or set of actions that process data in sequence. This means that the results or output from one segment of the system become the input for the next. The usual function of a data pipeline is to move data from one state or location to another."(SnapLogic) [source]
"A data pipeline is a software process that takes data from sources and pushes it to a destination. Most modern data pipelines are automated with an ETL (Extract, Transform, Load) platform." (Xplenty) [source]
"A data pipeline is a set of actions that extract data (or directly analytics and visualization) from various sources. It is an automated process: take these columns from this database, merge them with these columns from this API, subset rows according to a value, substitute NAs with the median and load them in this other database." (Alan Marazzi)
"A source and all the transformations and targets that receive data from that source. Each mapping contains one or more pipelines." (Informatica)
"An ETL Pipeline refers to a set of processes extracting data from an input source, transforming the data, and loading into an output destination such as a database, data mart, or a data warehouse for reporting, analysis, and data synchronization." (Databricks) [source]
"Data pipeline consists of a set of actions performed in real-time or in batches, that captures data from various sources, sorting it and then moving that data through applications, filters, and APIs for storage and analysis." (EAI)
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