Situation Description Is an Important Part of Competitive Intelligence
Issue:
Volume 4, Issue 2, June 2020
Pages:
25-29
Received:
31 December 2019
Accepted:
7 April 2020
Published:
29 April 2020
Abstract: A large number of existing publications on Competitive Intelligence focus on methodology level, and readers can learn very systematic and perfect theoretical models from them. However, for the fast developing emerging markets, the growing desire for competitive intelligence drives a large number of novices to enter this field and they need to start from the foundation level. Firstly they need to learn how to write a qualified intelligence by understanding some basic principles, which cannot be found from many industry publications. Based on this status, the author summarizes the basic elements of competitive intelligence by comparing different types of intelligence documents with examples, puts forward the six elements rule of competitive intelligence, i.e. FLOATS principle, and points out that the situational element is very important. Through literature review and practical examples, the author expounds the meaning of situation, points out that situation is the description of the whole competitive environment and the inherent characteristics of competitive intelligence. The author also compares declarative knowledge and process knowledge with situational knowledge, and discloses their differences. It shows that the situational knowledge reflects practical experience, which is very welcomed by all the practitioners. Therefore, situational description is one of the core elements of competitive intelligence, and it is worth the attention of novices.
Abstract: A large number of existing publications on Competitive Intelligence focus on methodology level, and readers can learn very systematic and perfect theoretical models from them. However, for the fast developing emerging markets, the growing desire for competitive intelligence drives a large number of novices to enter this field and they need to start...
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Construction and Management of Astronomical Big Data Analysis and Multi-dimensional Information Visualization Platform
Yang Zherui,
Gao Na,
Liu Liang
Issue:
Volume 4, Issue 2, June 2020
Pages:
30-40
Received:
10 March 2020
Accepted:
9 April 2020
Published:
29 April 2020
Abstract: The development of modern astronomy is rapidly and astronomical data increases exponentially. The HPC architecture based on GPU provides an efficient way of astronomic big data computing. Based on secure Ipv6 network environment, PMO has constructed the Big Data Analysis and Multi-dimensional Information Visualization Platform, which can reach the peak computing speed of 352Tflops and the totally storage capacity of 288TB. The platform is composed of 25 computing nodes, one management node and 5 storage nodes. The use of user-friendly, centralized cluster management software, the deployment of proprietary environmental control settings and multi-dimensional visualization of safety management systems form a multi-level, tridimensional and efficient management structure. A high-speed, high-capacity, highly reliable, secure and efficient high-performance computing cluster is finally constructed. The platform has a fully redundant, self-healing, highly scalable distributed storage system, a high-performance InfiniBand parallel computing and storage network, a complete job scheduling system, a cuda parallel computing architecture, and a variety of physical software tools for astronomical applications. It offers a great help to astronomical research topics such as astronomical image processing, moving target extraction, space target orbit calculation, numerical cosmology, cosmology simulation, galaxy fluid simulation. Thus it provides an important information support for the research work of 3 major breakthroughs and 5 key cultivation directions in the "One Three Five" plan of Purple Mountain Observatory.
Abstract: The development of modern astronomy is rapidly and astronomical data increases exponentially. The HPC architecture based on GPU provides an efficient way of astronomic big data computing. Based on secure Ipv6 network environment, PMO has constructed the Big Data Analysis and Multi-dimensional Information Visualization Platform, which can reach the ...
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