Clouds, big data, and smart assets: Ten tech-enabled business trends to watch

By W. Dutton, Kristofer S. J. Pister, Hal R. Varian, R. Bernard, Rob Salkowitz, J. Bughin, Michael Chui, J. Manyika. 2010

523 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9d42ff0ffd582cd11e6932356186fa97d9d9f878

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Citations in the corpus

The role of big data in smart city (2016, background): “New technologies can extend the reach of organizations, improve management decisions, and accelerate the development of new products and services (Bughin et al., 2010).”
Big Data in product lifecycle management (2015, background): “Moreover, with the increasing needs to build smart city, various kinds of data for optimizing the operation of the whole city are required [45].”
Data mining with big data (2016, background): “Such systems, even if the prediction accuracy is just slightly better than random guess, will bring significant business values to the developers [9].”
Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison (2018, background): “Data is becoming the important assets of human society, and big data era has come [10].”
Facilitating Agricultural Technology Adoption Among the Poor: The Role of Service Delivery Through Mobile Phones (2012, unknown): “3 Developers are increasingly making use of new technology trends (Bughin et al. 2011) to develop and deliver such m-services, complementing existing mobile technologies such as SMS and voice calls.”
The impact of big data on world-class sustainable manufacturing (2015, background): “BDA is one of the fastest evolving fields due to convergence of IoT, the cloud, and smart assets [12].”
Big Data and cloud computing: innovation opportunities and challenges (2017, background): “Several investigations have identified new initiatives for Big Data and cloud computing (Bughin, Chui, and Manyika 2010; Karimi 2014; Assunção et al. 2015; Hashem et al. 2015) from different facets of management/architecture, model development, visualization, interaction and business.”
Data management in cloud environments: NoSQL and NewSQL data stores (2013, background): “Today, businesses are aware that this huge volume of data can be used to generate new opportunities and process improvements through their processing and analysis [5,6].”
Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph (2015, background): “These varieties of data require different equipment and technology to handle and store (Bughin et al., 2010).”