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Semi-structured data. Semi-structured data[1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data ...
Unstructured data. Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text -heavy, but may contain data such as dates, numbers, and facts as well.
In statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts ...
Data science is an interdisciplinary academic field [1] that uses statistics, scientific computing, scientific methods, processing, scientific visualization, algorithms and systems to extract or extrapolate knowledge and insights from potentially noisy, structured, or unstructured data.
Because of the way it is produced and stored, this information is either unstructured or semi-structured. The management of semi-structured data is an unsolved problem in the information technology industry. [17] According to projections from Gartner (2003), white-collar workers spend 30–40% of their time searching, finding, and assessing ...
However, the change in type and nature from structured to semi-structured or unstructured challenged the existing tools and technologies. Big data technologies evolved with the prime intention to capture, store, and process the semi-structured and unstructured (variety) data generated with high speed (velocity), and huge in size (volume).
In statistics, data can have any of various statistical data types, e.g. categorical data (e.g. country), directional data (angles or directions, e.g. wind measurements), count data (a whole number of events), or real interval (e.g. measures of temperature). The data type is a fundamental concept in statistics, and controls what sorts of ...
Statistics (from German: Statistik, orig. "description of a state, a country" [1]) is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. [2] In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical ...