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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, a business plan for a non-profit might discuss the fit between the business plan and the organization's mission. Banks are quite concerned about defaults, so a business plan for a bank loan will build a convincing case for the organization's ability to repay the loan.
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.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
The lower parts of the walls of the 16th century dining hall of St John's College, Cambridge are covered with wood panelling in a linenfold design. An English oak chest with complex linenfold panels.
Business analysis is a professional discipline [1] focused on identifying business needs and determining solutions to business problems. [2] Solutions may include a software-systems development component, process improvements, or organizational changes, and may involve extensive analysis, strategic planning and policy development.
Our analysis focused primarily on subsidies — how much a school effectively “donates” or invests in its athletics department to make up for a lack of earned revenue. Subsidies can come from three sources: student fees, funds allocated by the school and government support.
In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions.