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Security Analytics
Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. Analytics also entails applying data patterns toward effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance. Organizations may apply analytics to business data to describe, predict, and improve business performance. Specifically, areas within analytics include descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics, and cognitive analytics. Analytics may apply to a variety of fields such as marketing, management, finance, online systems, information security, and software services. Since analytics can require extensive computation (see ...
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English Wikipedia's Traffic By Browser Family
English usually refers to: * English language * English people English may also refer to: Culture, language and peoples * ''English'', an adjective for something of, from, or related to England * ''English'', an Amish term for non-Amish, regardless of ethnicity * English studies, the study of English language and literature Media * English (2013 film), ''English'' (2013 film), a Malayalam-language film * English (novel), ''English'' (novel), a Chinese book by Wang Gang ** English (2018 film), ''English'' (2018 film), a Chinese adaptation * The English (TV series), ''The English'' (TV series), a 2022 Western-genre miniseries * English (play), ''English'' (play), a 2022 play by Sanaz Toossi People and fictional characters * English (surname), a list of people and fictional characters * English Fisher (1928–2011), American boxing coach * English Gardner (born 1992), American track and field sprinter * English McConnell (1882–1928), Irish footballer * Aid ...
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Academic Discipline
An academic discipline or academic field is a subdivision of knowledge that is taught and researched at the college or university level. Disciplines are defined (in part) and recognized by the academic journals in which research is published, and the learned society, learned societies and academic departments or faculties within colleges and universities to which their practitioners belong. Academic disciplines are conventionally divided into the humanities (including philosophy, Linguistics, language, art and cultural studies), the scientific disciplines (such as physics, chemistry, and biology); and the formal sciences like mathematics and computer science. The social sciences are sometimes considered a fourth category. It is also known as a ''field of study'', ''field of inquiry'', ''research field'' and ''branch of knowledge''. The different terms are used in different countries and fields. Individuals associated with academic disciplines are commonly referred to as ''expert ...
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Web Analytics
Web analytics is the measurement, data collection, collection, analysis, and reporting of web Data (computing), data to understand and optimize web usage. Web analytics is not just a process for measuring web traffic but can be used as a tool for business and market research and assess and improve website effectiveness. Web analytics applications can also help companies measure the results of traditional print or Broadcasting, broadcast advertising campaigns. It can be used to estimate how traffic to a website changes after launching a new advertising campaign. Web analytics provides information about the number of visitors to a website and the number of page views, or creates user behaviour profiles. It helps gauge traffic and popularity trends, which is useful for market research. Basic steps of the web analytics process Most web analytics processes come down to four essential stages or steps, which are: * data collection, Collection of data: This stage is the collection of th ...
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Google Analytics
Google Analytics is a web analytics service offered by Google that tracks and reports website traffic and also mobile app traffic and events, currently as a platform inside the Google Marketing Platform brand. Google launched the service in November 2005 after acquiring Urchin. As of 2019, Google Analytics is the most widely used web analytics service on the web. Site frequently updated. Google Analytics provides an SDK that allows gathering usage data from iOS and Android apps, known as ''Google Analytics for Mobile Apps''. Google Analytics has undergone many updates since its inception and is currently on its 4th iteration—GA4. GA4 is the default Google Analytics installation and is the renamed version for the (App + Web) Property that Google released in 2019 in a Beta form. GA4 has also replaced Universal Analytics (UA). One notable feature of GA4 is a natural integration with Google's BigQuery—a feature previously only available with the enterprise GA 360. This ...
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Sessionization
In web analytics, a session, or visit is a unit of measurement of a user's actions taken within a period of time or with regard to completion of a task. Sessions are also used in operational analytics and provision of user-specific recommendations. There are two primary methods used to define a session: time-oriented approaches based on continuity in user activity and navigation-based approaches based on continuity in a chain of requested pages. Definition The definition of "session" varies, particularly when applied to search engines. Generally, a session is understood to consist of "a sequence of requests made by a single end-user during a visit to a particular site". In the context of search engines, "sessions" and "query sessions" have at least two definitions. A session or query session may be all queries made by a user in a particular time period or it may also be a series of queries or navigations with a consistent underlying user need. Uses Sessions per user can b ...
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Web Analytics
Web analytics is the measurement, data collection, collection, analysis, and reporting of web Data (computing), data to understand and optimize web usage. Web analytics is not just a process for measuring web traffic but can be used as a tool for business and market research and assess and improve website effectiveness. Web analytics applications can also help companies measure the results of traditional print or Broadcasting, broadcast advertising campaigns. It can be used to estimate how traffic to a website changes after launching a new advertising campaign. Web analytics provides information about the number of visitors to a website and the number of page views, or creates user behaviour profiles. It helps gauge traffic and popularity trends, which is useful for market research. Basic steps of the web analytics process Most web analytics processes come down to four essential stages or steps, which are: * data collection, Collection of data: This stage is the collection of th ...
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Panel Data
In statistics and econometrics, panel data and longitudinal data are both multi-dimensional data involving measurements over time. Panel data is a subset of longitudinal data where observations are for the same subjects each time. Time series and cross-sectional data can be thought of as special cases of panel data that are in one dimension only (one panel member or individual for the former, one time point for the latter). A literature search often involves time series, cross-sectional, or panel data. A study that uses panel data is called a longitudinal study or panel study. Example In the multiple response permutation procedure (MRPP) example above, two datasets with a panel structure are shown and the objective is to test whether there's a significant difference between people in the sample data. Individual characteristics (income, age, sex) are collected for different persons and different years. In the first dataset, two persons (1, 2) are observed every year for three ...
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Principal Component Analysis
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified. The principal components of a collection of points in a real coordinate space are a sequence of p unit vectors, where the i-th vector is the direction of a line that best fits the data while being orthogonal to the first i-1 vectors. Here, a best-fitting line is defined as one that minimizes the average squared perpendicular distance from the points to the line. These directions (i.e., principal components) constitute an orthonormal basis in which different individual dimensions of the data are linearly uncorrelated. Many studies use the first two principal components in order to plot the data in two dimensions and to visually identi ...
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Cluster Analysis
Cluster analysis or clustering is the data analyzing technique in which task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more Similarity measure, similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistics, statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis refers to a family of algorithms and tasks rather than one specific algorithm. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small Distance function, distances between cluster members, dense areas of the data space, intervals or pa ...
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Unsupervised Learning
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks in the spectrum of supervisions include weak- or semi-supervision, where a small portion of the data is tagged, and self-supervision. Some researchers consider self-supervised learning a form of unsupervised learning. Conceptually, unsupervised learning divides into the aspects of data, training, algorithm, and downstream applications. Typically, the dataset is harvested cheaply "in the wild", such as massive text corpus obtained by web crawling, with only minor filtering (such as Common Crawl). This compares favorably to supervised learning, where the dataset (such as the ImageNet1000) is typically constructed manually, which is much more expensive. There were algorithms designed specifically for unsupervised learning, such as clustering algorithms like k-means, dimensionality reduction techniques l ...
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Forbes
''Forbes'' () is an American business magazine founded by B. C. Forbes in 1917. It has been owned by the Hong Kong–based investment group Integrated Whale Media Investments since 2014. Its chairman and editor-in-chief is Steve Forbes. The company is headquartered in Jersey City, New Jersey. Sherry Phillips is the current CEO of Forbes as of January 1, 2025. Published eight times per year, ''Forbes'' feature articles on finance, industry, investing, and marketing topics. It also reports on related subjects such as technology, communications, science, politics, and law. It has an international edition in Asia as well as editions produced under license in 27 countries and regions worldwide. The magazine is known for its lists and rankings, including its lists of the richest Americans (the Forbes 400, ''Forbes'' 400), of 30 notable people under the age of 30 (the Forbes 30 Under 30, ''Forbes'' 30 under 30), of America's wealthiest celebrities, of the world's top companies (the Fo ...
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Predictive Modeling
Predictive modelling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. In many cases, the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam. Models can use one or more classifiers in trying to determine the probability of a set of data belonging to another set. For example, a model might be used to determine whether an email is spam or "ham" (non-spam). Depending on definitional boundaries, predictive modelling is synonymous with, or largely overlapping with, the field of machine learning, as it is more commonly referred to in academic or research and development contexts. ...
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