Big data


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Big data

| created by janarez | Add resource "The Pathologies of Big Data"
Title
Big data
Description
Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many fields (columns) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. Therefore, big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value.
Link
https://en.wikipedia.org/?curid=27051151

resources

compared in The Pathologies of Big Data
v1 | attached by janarez | Add resource "The Pathologies of Big Data"

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topics

relates to Machine learning
v1 | attached by janarez | Add resource "The Pathologies of Big Data"
relates to Deep learning
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uses Apache Hadoop
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uses Apache Spark
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uses Big data framework
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