Cloud intelligence: what is REALLY new?
Proceedings of the 1st International Workshop on Cloud Intelligence
Daisy: the center for data-intensive systems at Aalborg University
ACM SIGMOD Record
Business Intelligence and the Web
Information Systems Frontiers
On-demand multidimensional data integration: toward a semantic foundation for cloud intelligence
The Journal of Supercomputing
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Cloud intelligence is a collection of technologies emerging from the migration of business intelligence and analytics technologies to a cloud computing environment combined with exploiting the massive range of new intelligence opportunities opened up by cloud computing. With cloud computing, we have to handle a paradigm shift in the computing infrastructure. Here, existing concepts such as storage, processes, computation, etc., are virtualized to all be parts of the cloud. Thus, technologies have to become device and location independent, e.g., different parts of the data will all reside in the cloud, but can be dispersed, and even migrating, between many physical locations and devices. We thus have to start thinking about data management as a service, which in turn entails that analytics and intelligence also become services. Another aspect of cloud intelligence is that every service potentially should be scalable to a global level, meaning that massively parallel computing techniques such map-reduce and beyond will become the standard programming model. Cloud intelligence also entails agility, the ability to assemble the necessary resources on demand, not only in terms of computing power, but also in terms of data sources. In a long term perspective, all the data in the world is available in the cloud, some in public clouds, including the web, some only in private clouds, and some in hybrids. Thus, the current significant difference between own and public data instead becomes a sliding grey scale. This development poses many challenges to cloud intelligence: with sensitive data outsourced to a cloud provider, privacy and security becomes essential parts of any analytics solution; with the increasing dependence on cloud computing, reliability becomes mission-critical; and cloud intelligence also needs to become energy-aware to reduce the massive energy consumption in data centers. Finally, the perhaps greatest challenge comes from fully utilizing all the new (types of) data available in cloud, for an ever increasing range of intelligence functionality to many more and much more diverse users.