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Analytics is the systematic computational analysis of data or statistics[1]. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It 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.<ref>Template:Cite web</ref> 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 big data), the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics.<ref>Template:Cite journal</ref> According to International Data Corporation, global spending on big data and business analytics (BDA) solutions is estimated to reach $215.7 billion in 2021.<ref>Template:Cite web</ref><ref>Template:Cite web</ref> As per Gartner, the overall analytic platforms software market grew by $25.5 billion in 2020.<ref>Template:Cite web</ref>

Analytics Glossary Wiki Overview

Template:Confusing sectionData analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment.<ref name=":0">Template:Cite book</ref> It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.<ref>Template:Cite web</ref>Template:Unreliable source? Data analytics is used to formulate larger organizational decisions. Template:Citation needed

Data analytics is a multidisciplinary field. There is extensive use of computer skills, mathematics, statistics, the use of descriptive techniques and predictive models to gain valuable knowledge from data through analytics.Template:Cn There is increasing use of the term advanced analytics, typically used to describe the technical aspects of analytics, especially in the emerging fields such as the use of machine learning techniques like neural networks, decision trees, logistic regression, linear to multiple regression analysis, and classification to do predictive modeling.<ref name="forbes2">Template:Cite web</ref><ref name=":0" /> It also includes unsupervised machine learning techniques like cluster analysis, Principal Component Analysis, segmentation profile analysis and association analysis.Template:Cn

Glossary

Analytics Domain

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Data and Analytics

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Analtyics Methods and Functions

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Analtyics Processes

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Analytics Tools and Technology

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Analytics Use Cases

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Analytics Governance

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Analytics Metrics and Evaluation

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Analytics Integration and Deployment

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Analytics Collaboration and Communication

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External links

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