Big Data

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10 Terms

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Big Data
Datasets that are so large or complex that traditional data processing applications cannot handle them effectively.
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The three Vs of Big Data
Volume, Velocity, and Variety; these define the characteristics and challenges of big data.
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Volume
Refers to the vast amounts of information in big data, often exceeding terabytes or petabytes.
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Velocity
Describes the speed at which data is generated and needs to be processed, often in near real-time.
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Variety
Indicates the various forms of data in big data, including structured, semi-structured, and unstructured formats.
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Functional Programming
A programming paradigm that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data.
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Fact-based model
A representation method where each data point is an immutable fact, timestamped to prevent overwriting previous data.
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Graph Schema
A visual representation of data relationships through nodes and edges, where nodes represent entities and edges represent relationships.
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Data Mining
A technique used to derive actionable insights from big data by identifying patterns and relationships.
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Machine Learning
An advanced technique for analyzing big data that enables systems to learn from data and make predictions.