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Big data. Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...
Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information ...
A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision. The figure is an example of the interaction between process and data models.
Data-intensive computing. Data-intensive computing is a class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes or petabytes in size and typically referred to as big data. Computing applications that devote most of their execution time to computational requirements are ...
Linked open data are linked data that are open data. [ 5 ] [ 6 ] [ 7 ] Tim Berners-Lee gives the clearest definition of linked open data as differentiated from linked data. Linked Open Data (LOD) is Linked Data which is released under an open license, which does not impede its reuse for free.
Data ecosystem. A data ecosystem is the complex environment of co-dependent networks and actors that contribute to data collection, transfer and use. [ 1 ] It can span multiple sectors – such as healthcare or finance, to inform one another's practices. [ 2 ] A data ecosystem often consists of numerous data assemblages. [ 3 ]
Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g., points, lines, or bars) contained in graphics. The goal is to communicate information clearly and efficiently to users. It is one of the steps in data analysis or data science. According to Vitaly Friedman (2008) the "main ...