data - significado y definición. Qué es data
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Qué (quién) es data - definición

INFORMATION ARRANGED FOR AUTOMATIC PROCESSING
Statistical data; Golden Source of data; Scientific data; Data value; Research data; Datum; Data (information); 🆥
  • These are some of the different types of data.

data         
n.
1) to feed in; process; retrieve; store data
2) to cite; evaluate; gather data
3) biographical; raw; scientific; statistical data USAGE NOTE: Purists insist on the data are available and consider the data is available to be incorrect.
Data         
·pl of Datum.
II. Data ·noun ·pl ·see Datum.
data         
Frequency: The word is one of the 1500 most common words in English.
1.
You can refer to information as data, especially when it is in the form of facts or statistics that you can analyse. In American English, data is usually a plural noun. In technical or formal British English, data is sometimes a plural noun, but at other times, it is an uncount noun.
The study was based on data from 2,100 women...
To cope with these data, hospitals bought large mainframe computers.
N-UNCOUNT; also N-PLURAL
2.
Data is information that can be stored and used by a computer program. (COMPUTING)
You can compress huge amounts of data on to a CD-ROM.
N-UNCOUNT

Wikipedia

Data

In the pursuit of knowledge, data (US: ; UK: ) is a collection of discrete values that convey information, describing quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data is commonly used in scientific research, economics, and in virtually every other form of human organizational activity. Examples of data sets include price indices (such as consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents the raw facts and figures which can be used in such a manner in order to capture the useful information out of it.

Data is collected using techniques such as measurement, observation, query, or analysis, and typically represented as numbers or characters which may be further processed. Field data is data that is collected in an uncontrolled in-situ environment. Experimental data is data that is generated in the course of a controlled scientific experiment. Data is analyzed using techniques such as calculation, reasoning, discussion, presentation, visualization, or other forms of post-analysis. Prior to analysis, raw data (or unprocessed data) is typically cleaned: Outliers are removed and obvious instrument or data entry errors are corrected.

Data can be seen as the smallest units of factual information that can be used as a basis for calculation, reasoning, or discussion. Data can range from abstract ideas to concrete measurements, including but not limited to, statistics. Thematically connected data presented in some relevant context can be viewed as information. Contextually connected pieces of information can then be described as data insights or intelligence. The stock of insights and intelligence that accumulates over time resulting from the synthesis of data into information, can then be described as knowledge. Data has been described as "the new oil of the digital economy". Data, as a general concept, refers to the fact that some existing information or knowledge is represented or coded in some form suitable for better usage or processing.

Advances in computing technologies have led to the advent of big data, which usually refers to very large quantities of data, usually at the petabyte scale. Using traditional data analysis methods and computing, working with such large (and growing) datasets is difficult, even impossible. (Theoretically speaking, infinite data would yield infinite information, which would render extracting insights or intelligence impossible.) In response, the relatively new field of data science uses machine learning (and other artificial intelligence (AI)) methods that allow for efficient applications of analytic methods to big data.

Ejemplos de uso de data
1. The scientific data is converted to digital computer data which can be run against similar data from unsolved cases.
2. Unemployment data disappoint The two biggest eurozone economies recorded disappointing labour data yesterday.
3. But there are very significant systematic data, as well as important generalized assessments and anecdotal data.
4. "I have not just a mountain of data, perhaps a mountain range of data.
5. New data The new estimate was based on more accurate satellite data.