Principal Component Analysis in Business Intelligence Applications

With the enormous amount of information available on the web, many innovative applications in the domain of business intelligence have emerged. Information regarding market trends, consumer profile, competitors, etc., enables a firm to chart its direction and formulate strategies. However, in this big data era, getting the right information is not an easy task. In this work, we introduce business intelligence (BI) applications in general, and examine the use of principal component analysis (PCA) in these applications. A study case reveals how PCA can be used for identification of relevant keywords as prominent features, as well as reducing the search space for an individual´s specific requests, in the context of a BI recommender.