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Web analytics is the measurement, collection, analysis, and reporting of web data to understand and optimize web usage. [1] 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.
Business intelligence (BI) consists of strategies, methodologies, and technologies used by enterprises for data analysis and management of business information. [1] Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text ...
Business analytics (BA) refers to the skills, technologies, and practices for iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods .
For example, you can have data be displayed within a map. By clicking a specific state or city you can get a closer look at the data contained within that location. Filters and parameters can also be added. For example, if one were to analyze revenues across the United States you could set a parameter to only show salaries within a particular ...
The maturity levels for business intelligence are: operational reporting; analytic reporting; business dashboards; analytic applications; It may extend further to predictive analytics, or predictive analysis may form part of the analytic application - depending on both the subject matter under analysis, and the nature of the analysis required.
Google Analytics provides a path function with funnels and goals. A predetermined path of web site pages is specified and every visitor walking the path is a goal. This approach is very helpful when analyzing how many visitors reach a certain destination page, called an end point analysis. [2]
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] 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.
Augmented Analytics is an approach of data analytics that employs the use of machine learning and natural language processing to automate analysis processes normally done by a specialist or data scientist. [1] The term was introduced in 2017 by Rita Sallam, Cindi Howson, and Carlie Idoine in a Gartner research paper. [1] [2]