Business Analytics Blogs

Application of Statistics in Business

Posted by: Dilip D | Business Analyitics

The field of statistics has numerous applications in business. Because of technological advancements, large amounts of data are generated by business these days. These data are now being used to make decisions. These better decisions we make help us improve the running of a department, a company , or the entire economy.
As per Philip Kotler and Gary Armstrong marketing “ identifies customer needs and wants , determine which target markets the organisations can serve best, and designs appropriate products, services and Programs to serve these markets”

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Business Analytics (BA) – A Tool for Business Excellence

Posted by: Dr. Tamilselvi | Business Analyitics

Business Intelligence (BI) is the process of collecting information from the different sources and preparing Business Reports, dashboards, scorecards, ad hoc query and automated alerts. It is the first step for the companies to make data driven decisions. Business Analytics (BA) starts with the analysis of the BI report through statistical analysis & data mining, extends to predictive model building with historical data and further validates it with model testing.

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Multivariate Statistical Techniques

Posted by: Dilip D | Business Analyitics

Multivariate analysis (MVA) is based on the statistical principle of multivariate statistics, which involves observation and analysis of more than one statistical outcome variable at a time1. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest.

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Why data visualization is important and how it helps business to make smarter decisions?

Posted by: Dr. Tamilselvi | Business Analyitics

Data Visualization is an important component and a perfect procedure for the accomplishment of an organization’s success in today’s uncertain market. Visualizing data using the right methods can provide insights which the decision makers can incorporate in their decision-making pipeline in order to make informed decisions which are driven by data.

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