The term ‘big data’ is used to describe data that are beyond the capabilities of an organization to store, analyze and use for accurate and timely decision making. They have alternately been described in terms of characteristics of volume, velocity, variety, veracity. We propose another characteristic of volatility for big data that should be considered in their use for decision making. We utilize a case study approach with a mid-sized company in the hospitality industry to elucidate challenges that an organization faces in developing a big data strategy and highlight research needed in this domain. Challenges identified were technical (inconsistent and unstandardized data, implementation and use of new analytics platforms, obtaining a global view of data, visualization of data, integrating mobile data), organizational (finding people with the right skills, users' desire for customization), and strategic management (finding return on investment in big data, alignment of business and analytics strategies, leadership of analytics initiatives and thought). Decision questions to be addressed in using big data for a marketing decision are illustrated. We demonstrate the use of the decision framework and illustrate challenges identified in the case study with sentiment analysis of Twitter data.
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