ABSTRACT
Many cities across the globe are adopting smart city initiatives, as smart city holds the promise of better quality of life and equity for city's residents, more efficient use of city's infrastructure, and more effective city planning. Big data analytics is the backbone of smart city and the drive engine to achieve smart city's promises. However, statistics indicate that more than 50% of big data projects fail; they either never finish or do not offer the expected value. Resulting in severe consequences as such projects tends to be expensive and require allocating the organization's best resources while doing the project. This is even more crucial in the case of smart city, as cities usually have limited budget and resources.
This paper conducted literature review and perspectives analysis to identify challenges, which can cause big data projects to fail, with focus on smart city related big data projects. The goal is to offer a list of challenges, that a project manager can consider as an initial list of risks for the upcoming project, and evaluate the city's readiness against each of them.
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