Business Intelligence

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business-intelligence

Category Description

Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes. BI technologies are capable of handling large amounts of unstructured data to help identify, develop and otherwise create new strategic business opportunities.
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Latest Thoughts

2327

Lack of Data Integrity and Law Enforcement

Posted on by Kathleen Marrs, Ph.D.
Briggs, L. (2007). BI case study: Cleaner data allows better policing. Business Intelligence Journal 12(2), pp. 48-50.

Briggs (2007) explained that as organizations have learned to quickly amass volumes of data to support decision making, ensuring that the data is reliable has become increasingly challenging. Briggs’ study focused on how the Humberside Police force in the U.K. had addressed the challenges. The vision of Humberside was to not only improve its data warehousing system to produce better intelligence, but to standardize the data that is extracted from a number of disparate internal and external databases toward the goal of being able to share vital police information among more than 43 jurisdictions throughout the U.K.

2242

Using Logistic Regression to Estimate Credit Card Profitability

Posted on by Kathleen Marrs, Ph.D.
So, M. C., Thomas, L.C., Seow, H-V, & Mues, C. (2014). Using a transactor/revolver scorecard to make credit and pricing decisions. Decision Support Systems 59(2014), pp. 143-151.

So, Thomas, Seow, and Mues (2014) developed a logistic regression model for estimating the profitability of consumers’ use of credit cards using a transactor/revolver scorecard and explained how such a scorecard can be used as part of a risk assessment system. Building a scorecard that enables credit card issuers to classify an applicant as either good (low risk) or bad (high risk) has been the traditional approach to deciding whether or not to extend credit. According to the authors, credit card companies could better inform their decisions by also distinguishing between transactors and revolvers, or between those who pay off their balances to avoid interest charges and those who do not. The authors argued that while transactors are inherently good, they are also less profitable than revolvers and by scoring applicants along both good/bad and transactor/revolver dimensions can help credit card issuers make pricing decisions and more accurately estimate profits.

2219

Using Text Regression for Predicting Usefulness of Customer Opinion

Posted on by Kathleen Marrs, Ph.D.
Ngo-Ye, T. L. & Sinha, A. P. (2014). The influence of reviewer engagement characteristics on online review helpfulness: A text regression model. Decision Support Systems 61(2014), pp. 47-58.

Ngo-Ye and Sinha (2014) developed a text regression model for predicting the helpfulness of 7,465 online restaurant reviews posted at Yelp.com and 584 book reviews posted at Amazon.com. According to the authors, most review opinion mining studies focused on sentiment rather than quality and ignored reviewer engagement characteristics. The authors argued that reviewer characteristics influence the perception of helpfulness and that decision makers at online organizations who rely on user-generated content to gain marketing advantage could better leverage that content if they understood what makes it helpful to others and if they could predict that helpfulness.