Significant research challenges must be addressed in the cleaning, transformation, integration, modeling, and analytics of Big Data sources for finance. This article surveys the progress made so far in this direction and obstacles yet to be overcome. These are issues that are of interest to data-...
Data analytics in auditing Opportunities and challenges审计中数据分析的机遇与挑战1.pdf,BUSHOR-1226; No. of Pages 8 Business Horizons (2015) xxx , xxx—xxx Available online at ScienceDirect /locate/bushor Data analytics in auditing: Opportunities and chal
Long-read technologies are overcoming early limitations in accuracy and throughput, broadening their application domains in genomics. Dedicated analysis tools that take into account the characteristics of long-read data are thus required, but the fast pace of development of such tools can be overwhelmin...
data leaders had dedicated teams or roles to monitor and evaluate the impact of global regulations. Modern infrastructure can help as well, one leader told us: “Most of our critical infrastructure is new, automated, and in public cloud, which gives us an advantage in terms of agility. We ...
Sound data analysis is critical to the success of modern molecular medicine research that involves collection and interpretation of mass-throughput data. The novel nature and high-dimensionality in such datasets pose a series of non-trivial data analysis problems. This technical commentary discusses the...
Second, modern computational methods and tools are being developed which add further capability to traditional statistical analysis tools. These two developments have created a new range of problems and challenges for analysts, as well as new opportunities for intelligent systems in data analysis. 关键...
Critical analysis for big data studies in construction: significant gaps in knowledge The main themes discussed were big data as a concept, big data analytical methods/techniques, big data opportunities - challenges and big data application... UH Madanayake,C Egbu - 《Built Environment Project &...
As artificial intelligence (AI) transitions from research to deployment, creating the appropriate datasets and data pipelines to develop and evaluate AI models is increasingly the biggest challenge. Automated AI model builders that are publicly available can now achieve top performance in many applications...
We are living in an era of data deluge and as a result, the term ``big data'' is appearing in many contexts, from meteorology, genomics, complex physics simulations, biological and environmental research, finance and business to healthcare. As the name implies, big data literally means large...
Data-Intensive Science and Engineering(DISE),ranging from data storage and organization,computational method,data analysis,to user interfaces.Meanwhile,data quality,data security and data curation should be paid more attentions.In this paper,we attempt to describe the architecture of DISE,review the ...