Big data


Topic | v1 | created by janarez |
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.


Relations

relates to Artificial intelligence (AI)

Artificial intelligence (AI), is intelligence demonstrated by machines, unlike the natural intelligen...

relates to Deep learning

Deep learning (also known as deep structured learning) is part of a broader family of machine learnin...

relates to Machine learning

Machine learning (ML) is the study of computer algorithms that improve automatically through experien...

uses Apache Hadoop

Apache Hadoop is a collection of open-source software utilities that facilitates using a network of m...

uses Apache Spark

Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provid...

uses Big data framework

Frameworks for processing Big data.


Edit details Edit relations Attach new author Attach new topic Attach new resource
Resources

compared in The Pathologies of Big Data

10.0 rating 1.0 level 10.0 clarity 7.0 background – 1 rating

Scale up your datasets enough and all your apps will come undone. What are the typical problems and...