Analytics

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.

[3] Analytics may apply to a variety of fields such as marketing, management, finance, online systems, information security, and software services.

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.

[citation needed] 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.

[citation needed] Marketing organizations use analytics to determine the outcomes of campaigns or efforts, and to guide decisions for investment and consumer targeting.

[11] Marketing analytics consists of both qualitative and quantitative, structured and unstructured data used to drive strategic decisions about brand and revenue outcomes.

The data enables companies to make predictions and alter strategic execution to maximize performance results.

[11] Web analytics allows marketers to collect session-level information about interactions on a website using an operation called sessionization.

[17] The aim is to discern which employees to hire, which to reward or promote, what responsibilities to assign, and similar human resource problems.

[18] For example, inspection of the strategic phenomenon of employee turnover utilizing people analytics tools may serve as an important analysis at times of disruption.

[21] However, experts find that many HR departments are burdened by operational tasks and need to prioritize people analytics and automation to become a more strategic and capable business function in the evolving world of work, rather than producing basic reports that offer limited long-term value.

[23] Examples of HR analytic metrics include employee lifetime value (ELTV), labour cost expense percent, union percentage, etc.

[citation needed] Predictive models in the banking industry are developed to bring certainty across the risk scores for individual customers.

[27] It is also extensively used in financial institutions like online payment gateway companies to analyse if a transaction was genuine or fraud.

[33][34] Products in this area include security information and event management and user behavior analytics.

One such innovation is the introduction of grid-like architecture in machine analysis, allowing increases in the speed of massively parallel processing by distributing the workload to many computers all with equal access to the complete data set.