What is Analytics

A structured process of reviewing data in a logical and detailed manner to derive meaning and understanding that would result in sensemaking.

The systematic computational analysis of data or statistics or information resulting from the systematic analysis of data or statistics.

It is the process of analyzing data belonging to specific domain using analytical tools.

The process of analyzing data to discover, interpret and communicate significant patterns or insights to eventually drive or influence decision-making. Learning Analytics is the measurement, collection, analysis and reporting of data for purposes of understanding and optimizing learning and the environments in which it occurs.

Information resulting from the systematic analysis of data or statistics.

Data that a software can provide to help uncover valuable data about your users.

Has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen.

Analytics is defined as the scientific process of transforming data into insight for making better decisions.

As emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain, and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.

Collecting, processing, and analyzing data to obtain insights and make informed decisions.

The discovery and communication of patterns – with significance – in data.

Refers to data-driven analysis using various methods such as data mining and statistical techniques to provide better decision making.

Has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.

The process of transforming data into insight for the purpose of making decisions.

The collection and analysis of educational data to inform future instructional decisions.

Is the process of analyzing single or multiple sets of big or small data to discover meaningful pattern in them. Refer to the definition of big-data analytics, business case analytics, and small-data analytics.

Analytics represents a combination of computational technologies, scientific management techniques, and statistics to solve real-world problems, while considering that organizations have to analyze their data to understand what is happening, what will happen, and how to take the best option.

Davenport et al. (2007) AU15: The in-text citation "Davenport et al. (2007)" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. describe analytics as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions” (p. 7).

Software-based algorithms and statistics used to derive meaning from data.

A multidisciplinary field that explores, infers and communicates patterns in data.

Emerged as a catch-all term for a variety of different business intelligence (BI)- and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (e.g., sales, service, supply chain and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores, and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.

The science of discovering and communicating meaningful patterns in data and developing actionable plans. The Analytics paradigm often favors data visualization methods in reporting results and recommendations. Typically, Analytics consists of three board categories: descriptive, predictive and prescriptive.

The analysis and evaluation of data for the purposes of diagnosing, predicting, or prescribing actions.

Application of data mining and operations research for predictions, performance evaluations, comparisons, and optimal decision making.

Has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.

Has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as Website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain, and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.

Consumer behavioral data related to their platform usage behaviors such as the number of visits to a platform, time spent on the platform, and actions when using the platform. Using these behavioral data, advertisers and marketers are able to segment target audience to increase their experiences and to improve campaign effectiveness.

Analytics involves analysis of the data stream through systematic processing to infer and interpret the information contained in it for data pattern recognition and decision making.

Analytics is the process of statistics in which the data revelation, perception, and communication of meaningful patterns in data is obtained.

The discovery, interpretation and communication of meaningful patterns in data.

Has emerged as a catch-all term for a variety of different business intelligence (BI) and application-related initiatives. For some, it is the process of analyzing information from a particular domain, such as website analytics. For others, it is applying the breadth of BI capabilities to a specific content area (for example, sales, service, supply chain and so on). In particular, BI vendors use the “analytics” moniker to differentiate their products from the competition. Increasingly, “analytics” is used to describe statistical and mathematical data analysis that clusters, segments, scores and predicts what scenarios are most likely to happen. Whatever the use cases, “analytics” has moved deeper into the business vernacular. Analytics has garnered a burgeoning interest from business and IT professionals looking to exploit huge mounds of internally generated and externally available data.

A method to do systematic analysis of data/information.

The discovery and transmission of patterns in data that are meaningful based on the context of data.

The systematic computational analysis of data or statistics.

The primary technology that facilitates decision making, along with other components, such as search and reporting. The key platform capabilities of Analytics are Data collection, large volume Data Storage, Data synchronization, Data analysis and Reporting.

The field of data analysis. Analytics often involves studying past historical data to research potential trends, to analyze the effects of certain decisions or events, or to evaluate the performance of a given tool or scenario. The goal of analytics is to improve the business by gaining knowledge which can be used to make improvements or changes.

the extensive use of data, statistical and quantitative analysis, exploratory and predictive models, and fact-based management to drive decisions and actions.

In the IoT, analytics can be defined as the results achieved by analyzing data obtained through various intelligent devices.

The extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.

An umbrella term for data analysis applications. It is the use of “rocket science” algorithms (e.g., machine learning, neural networks) to analyze data.

Intensive use of structured and unstructured customer data whose quantitative and qualitative statistical exploitation, predictive and explanatory models allow to improve the decision-making process of companies and the creation of competitive advantages and generation of value in organizations.

Analytics is the processing of data, through IT, of a quantitative and qualitative type to help an organization better understand its businesses and markets (knowledge discovery) and to make timely business decisions.

The systematic analysis of data (thyroid dataset).

Systematic analysis of data or statistics.

Big Data analytics is the process of finding meaningful patterns or to get insight on data with extensive use of statistical and mathematical techniques.

Consumer behavioral data related to their platform usage behaviors such as the number of visits to a platform, time spent on the platform, and actions when using the platform. Using these behavioral data, advertisers and marketers are able to segment target audience to increase their experiences and to improve campaign effectiveness.

realizes information as competitive advantage. It is the process of analyzing single set or multiple sets of data to discover meaningful patterns in them. It facilitates the creation of the right solutions and the asking and answering of why to find the root causes in the chain of problems.

A data driven, manual analysis and optimization models including process that creates insight.

The use of large data sets and statistical analysis to answer questions and support decision making.