Data Mining and Data Warehousing in the Airline Industry

Abstract

Organizations are constantly looking to enhance their decision-making activities in order to improve business processes and build a competitive advantage. Each day they collect and store large amounts of data that may be analyzed to reduce costs, increase revenues, improve efficiencies, and predict future trends and customer behaviors. Data mining, which is the automated extraction of predictive information from large databases, helps connect large volumes of this heterogeneous data and allows organizations to analyze it from multiple perspectives. Designed for query and analysis rather than transaction processing, a data warehouse is a relational database that centralizes data coming from multiple sources. It translates information into common models, names, and definitions while also providing a mean to make information available for decision making. Although data mining and data warehousing are powerful tools for organizations they can present several challenges. The airline industry collects and stores large amount of heterogeneous data from a wide variety of sources. Studying the successes and failures of this industry to conduct data mining and data warehousing activities as airlines struggle in an increasingly competitive environment can be beneficial to other economic sectors as well.

Keywords: Data analysis, competitive advantage, prediction analysis, airline industry

JEL Classification: Z00