Search results
Results from the WOW.Com Content Network
The term big data has been in use since the 1990s, with some giving credit to John Mashey for popularizing the term. [22] [23] Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.
However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).
Revolution Analytics – production-grade software for the enterprise big data analytics; RStudio – GUI interface and development environment for R; ROOT – an open-source C++ system for data storage, processing and analysis, developed by CERN and used to find the Higgs boson; Salstat – menu-driven statistics software
Analytics is the application of mathematics and statistics to big data. Data scientists write analytics programs to look for solutions to business problems, like forecasting demand or setting an optimal price. The continuous approach runs multiple stateless engines which concurrently enrich, aggregate, infer and act on the data.
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."
Overabundance of already collected data became an issue only in the "Big Data" era, and the reasons to use undersampling are mainly practical and related to resource costs. Specifically, while one needs a suitably large sample size to draw valid statistical conclusions, the data must be cleaned before it can be used.
Leading 8-4, Houston used a 25-4 run to open up a 33-8 lead on a 3-pointer by Cryer with 1:16 remaining in the first half. Key stat Houston shot 43%, and Troy shot 24% and was 2 of 18 on 3-pointers.
Data-centric computing is an approach that merges innovative hardware and software to treat data, not applications, as the permanent source of value. [8] Data-centric computing aims to rethink both hardware and software to extract as much value as possible from existing and new data sources.