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2. Pipeline (computing) - Wikipedia

   en.wikipedia.org/wiki/Pipeline_(computing)

   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 ...

3. Pipeline Open Data Standard - Wikipedia

   en.wikipedia.org/wiki/Pipeline_Open_Data_Standard

   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.

4. Pipeline Pilot - Wikipedia

   en.wikipedia.org/wiki/Pipeline_pilot

   Pipeline Pilot is a software tool designed for data manipulation and analysis. It provides a graphical user interface for users to construct workflows that integrate and process data from multiple sources, including CSV files, text files, and databases. The software is commonly used in extract, transform, and load (ETL) tasks.

5. Pipeline (software) - Wikipedia

   en.wikipedia.org/wiki/Pipeline_(software)

   In software engineering, a pipeline consists of a chain of processing elements (processes, threads, coroutines, functions, etc.), arranged so that the output of each element is the input of the next. The concept is analogous to a physical pipeline .

6. Multiple instruction, single data - Wikipedia

   en.wikipedia.org/wiki/Multiple_instruction...

   In computing, multiple instruction, single data (MISD) is a type of parallel computing architecture where many functional units perform different operations on the same data. Pipeline architectures belong to this type, though a purist might say that the data is different after processing by each stage in the pipeline.

7. Extract, transform, load - Wikipedia

   en.wikipedia.org/wiki/Extract,_transform,_load

   The architecture for the analytics pipeline shall also consider where to cleanse and enrich data [10] as well as how to conform dimensions. [1] Some of the benefits of an ELT process include speed and the ability to more easily handle both unstructured and structured data.

8. KNIME - Wikipedia

   en.wikipedia.org/wiki/KNIME

   KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.

9. Hazard (computer architecture) - Wikipedia

   en.wikipedia.org/wiki/Hazard_(computer_architecture)

   Data hazards occur when instructions that exhibit data dependence modify data in different stages of a pipeline. Ignoring potential data hazards can result in race conditions (also termed race hazards). There are three situations in which a data hazard can occur: read after write (RAW), a true dependency; write after read (WAR), an anti-dependency