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Data lineage is a track of the life cycle of each piece of data as it is ingested, processed, and output by the analytics system. This provides visibility into the analytics pipeline and simplifies tracing errors back to their sources.
In computing, a pipeline or data pipeline [1] is a set of data processing elements connected in series, where the output of one element is the input of the next one. The elements of a pipeline are often executed in parallel or in time-sliced fashion. Some amount of buffer storage is often inserted between elements. Computer-related pipelines ...
The Pipeline Open Data Standard (PODS) Pipeline Data Model provides the database architecture pipeline operators use to store critical information and analysis data about their pipeline systems, and to manage this data geospatially in a linear-referenced database which can then be visualized in any GIS platform.
MIL-STD-498 standard describes the development and documentation in terms of 22 Data Item Descriptions (DIDs), which were standardized documents for recording the results of each the development and support processes, for example, the Software Design Description DID was the standard format for the results of the software design process.
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The captured lineage is combined and processed to obtain the data flow of the pipeline. The data flow helps the data scientist or a developer to look deeply into the actors and their transformations. This step allows the data scientist to figure out the part of the algorithm that is generating the unexpected output.
In software, an XML pipeline is formed when XML (Extensible Markup Language) processes, especially XML transformations and XML validations, are connected. For instance, given two transformations T 1 and T 2 , the two can be connected so that an input XML document is transformed by T 1 and then the output of T 1 is fed as input document to T 2 .
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