Research Publication Title

Chicago Building Code Violations Database Case Study

Major

Marketing

Faculty Mentor(s)

Dr. William Miller

Keywords

Building, Code, Violations, Employment, Income, Population

Abstract

Business Analytics (also known as the Big Data movement) and the ability of firms to use existing data bases in order to gain competitive advantage within their industry is a major force in business today. The Business Analytics Process suggests that firms take data bases through 3 stages: 1) a descriptive stage, where the data elements are analyzed as a start toward determining possible keep information from the data, 2) a predictive stage, where mathematical models are developed which test the statistical significance potential relationships observed from the first stage, and 3) a prescriptive stage where based on model results from the previous stage, firms operationalize what they have learned by making actual changes to their delivery systems through the development of heuristics, algorithms, software programs that allow them to effective use what they have found from the data in order to better delivery their product or service to their customer. In order to illustrate this process, this case study analyzes a data base involving building code violations in Chicago from 2006 to 2016. The data base was developed by the Chicago Department of Buildings and published by data.gov [https://catalog.data.gov/dataset/building-violations-f0f5e]. It includes variables like building code violations, date, address, and zip code of violations, violation description and, the inspector’s comments. We take the data through the descriptive stage of the three-step business analytics process. This study is an example of how businesses can use and adapt data to guide them when making tactical and strategic decisions. In the descriptive stage, we run frequencies and charts to visualize and understand the data. We could also merge other databases with our original to make the database more useful. While this presentation focuses on the descriptive stage, it would lead to the predictive stage where models would be developed that would predict a meaningful dependent variable like frequency of building code violations. Once a predictive model has been created, a company would use the results to influence their planning decisions which could lead them to achieve a competitive advantage in the marketplace.

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Chicago Building Code Violations Database Case Study

Business Analytics (also known as the Big Data movement) and the ability of firms to use existing data bases in order to gain competitive advantage within their industry is a major force in business today. The Business Analytics Process suggests that firms take data bases through 3 stages: 1) a descriptive stage, where the data elements are analyzed as a start toward determining possible keep information from the data, 2) a predictive stage, where mathematical models are developed which test the statistical significance potential relationships observed from the first stage, and 3) a prescriptive stage where based on model results from the previous stage, firms operationalize what they have learned by making actual changes to their delivery systems through the development of heuristics, algorithms, software programs that allow them to effective use what they have found from the data in order to better delivery their product or service to their customer. In order to illustrate this process, this case study analyzes a data base involving building code violations in Chicago from 2006 to 2016. The data base was developed by the Chicago Department of Buildings and published by data.gov [https://catalog.data.gov/dataset/building-violations-f0f5e]. It includes variables like building code violations, date, address, and zip code of violations, violation description and, the inspector’s comments. We take the data through the descriptive stage of the three-step business analytics process. This study is an example of how businesses can use and adapt data to guide them when making tactical and strategic decisions. In the descriptive stage, we run frequencies and charts to visualize and understand the data. We could also merge other databases with our original to make the database more useful. While this presentation focuses on the descriptive stage, it would lead to the predictive stage where models would be developed that would predict a meaningful dependent variable like frequency of building code violations. Once a predictive model has been created, a company would use the results to influence their planning decisions which could lead them to achieve a competitive advantage in the marketplace.