Data Analytics

What is data analytics?
The term data analytics is usually associated with the applications used to provide online analytical processing and reporting on business intelligence, but it can refer to a wider scope of techniques. Generally, data analytics refers to the process of using specialized software and tools to analyze sets of data in order to draw conclusions about the information they contain. [1] It is most commonly used by large companies to enhance productivity and business gain, but can also be used by researchers and scientists to verify or disprove theories and hypotheses.

Data analytics can be used to aid businesses to increase revenues, optimize marketing campaigns, improve operational efficiency, and react more quickly to emerging marketing trends to gain a competitive edge over rivals. [1] The data analyzed can come from sources both external and internal, and can be comprised of both new and historical information, all with the aim of improving a business’s performance.

Data Analytics Applications
Data analytics techniques are usually divided into two main categories, qualitative and quantitative. Quantitative data analysis refers to the analysis of data that has numerical values that can be compared statistically, and qualitative data analysis is the analysis of data sets that contain text, pictures, video, or audio, which cannot be measured statistically.

Additionally, data analytics techniques can be separated into two subsequent categories, exploratory data analysis (EDA) and confirmatory data analysis (CDA). EDA is usually to attempt to find patterns and relationships in a data set and can be compared to detective work, while CDA is the application of statistical techniques to determine whether a hypothesis about the data set is true or false and can be likened to the work of a judge and jury during a trial. [1]

Other more advanced types include techniques such as data mining, predictive analytics, machine learning, text mining, and big analytics. [1] Data mining refers to the process of mining through large sets of data to attempt to predict future trends, and predictive analysis similarly attempts to predict future equipment failures and customer behavior. Machine learning is a technique that uses artificial intelligence to quickly sort through large data sets faster than is normally possible with data scientists. [1] Similarly, text mining uses software to provide analysis of text-based data that would otherwise take very long to sort through manually. Finally, big data analytics applies some or all of these data analysis techniques to extremely large sets of data to draw conclusions about many forms of data.

See also: Intelligent Web

Resources
[1] "data analytics (DA)". SearchDataManagement.TechTarget.com. Retrieved 2017-4-13.