Download now Free registration required
Traditional data quality engineering techniques, often used and deployed within a single enterprise environment, are inadequate to cope with the rapid change of data, with a multitude of quality degrees, to be used in contemporary business models. The emerging cloud computing paradigm could potentially offer high-quality, composable data and techniques, under the Software-as-a-Service (SaaS), Data-asa-Service (DaaS) and crowdsourcing models, for data quality engineering and data publishing. However, so far how to utilize the potential of cloud computing models for data quality engineering has not been discussed. In this paper, one analyze requirements of data quality engineering and quality-aware data publishing processes in the cloud and one provide a conceptual architecture utilizing and supporting the SaaS, DaaS and crowdsourcing models for the realization of such processes.
- Format: PDF
- Size: 133.2 KB