This article is about the general concept. For files on IBM mainframes, see Data set (IBM mainframe). For data communications, see Modem.
Collection of data
Various plots of the multivariate data set Iris flower data set introduced by Ronald Fisher (1936).[1]
A data set (or dataset) is a collection of data. In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question. The data set lists values for each of the variables, such as for example height and weight of an object, for each member of the data set. Data sets can also consist of a collection of documents or files.[2]
In the open data discipline, data set is the unit to measure the information released in a public open data repository. The European data.europa.eu portal aggregates more than a million data sets.[3]
^Cite error: The named reference fisher36 was invoked but never defined (see the help page).
^Snijders, C.; Matzat, U.; Reips, U.-D. (2012). "'Big Data': Big gaps of knowledge in the field of Internet". International Journal of Internet Science. 7: 1–5. Archived from the original on 2019-11-23. Retrieved 2017-02-10.
^"European open data portal". European open data portal. European Commission. Retrieved 2016-09-23.
A dataset (or dataset) is a collection of data. In the case of tabular data, a dataset corresponds to one or more database tables, where every column...
The Iris flower dataset or Fisher's Iris dataset is a multivariate dataset used and made famous by the British statistician and biologist Ronald Fisher...
Examples of datasets include price indices (such as consumer price index), unemployment rates, literacy rates, and census data. In this context, data represents...
Big data primarily refers to datasets that are too large or complex to be dealt with by traditional data-processing application software. Data with many...
In databases, change data capture (CDC) is a set of software design patterns used to determine and track the data that has changed (the "deltas") so that...
The Common DataSet (CDS) is an annual product of the Common DataSet Initiative, "a collaborative effort among data providers in the higher education...
create insights from data. Data science is an interdisciplinary field focused on extracting knowledge from typically large datasets and applying the knowledge...
also be reviewed. There are several types of data cleaning, that are dependent upon the type of data in the set; this could be phone numbers, email addresses...
Data.gov, Data.gov.uk and Data.gov.in. Open data can be linked data - referred to as linked open data. One of the most important forms of open data is...
Data mining is the process of extracting and discovering patterns in large datasets involving methods at the intersection of machine learning, statistics...
the number of clusters in a dataset, a quantity often labelled k as in the k-means algorithm, is a frequent problem in data clustering, and is a distinct...
The Minimum DataSet (MDS) is part of the U.S. federally mandated process for clinical assessment of all residents in Medicare or Medicaid certified nursing...
Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database...
algorithm for predicting ratings by 10.06%. Netflix provided a training dataset of 100,480,507 ratings that 480,189 users gave to 17,770 movies. Each training...
process of data dredging involves testing multiple hypotheses using a single dataset by exhaustively searching—perhaps for combinations of variables that might...
potential uses. Data wrangling typically follows a set of general steps which begin with extracting the data in a raw form from the data source, "munging"...
for use by others. It is a practice consisting in preparing certain data or dataset(s) for public use thus to make them available to everyone to use as...
Minimum DataSet (NMDS) is a classification system which allows for the standardized collection of essential nursing data. The collected data are meant...
set of numbers is the value separating the higher half from the lower half of a data sample, a population, or a probability distribution. For a data set...
standardized data entities. As a result of recasting multiple data models, the set of recast data models will now share one or more commonality relationships...
The Healthcare Effectiveness Data and Information Set (HEDIS) is a widely used set of performance measures in the managed care industry, developed and...
exploratory data analysis (EDA) is an approach of analyzing datasets to summarize their main characteristics, often using statistical graphics and other data visualization...
Data visualization is concerned with visually presenting sets of primarily quantitative raw data in a schematic form. The visual formats used in data...
threshold or the number of expected clusters) depend on the individual dataset and intended use of the results. Cluster analysis as such is not an automatic...
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