ВОЗМОЖНОСТИ СИСТЕМ ОПЕРАТИВНОГО АНАЛИЗА ДАННЫХ ДЛЯ ИНТЕНСИФИКАЦИИ ПРОЦЕССА КОММЕРЦИАЛИЗАЦИИ ИННОВАЦИЙ

Переведенцев Д.А.

Аспирант, ФГБОУ ВПО «Ижевский Государственный Технический Университет им. М.Т. Калашникова»

ВОЗМОЖНОСТИ СИСТЕМ ОПЕРАТИВНОГО АНАЛИЗА ДАННЫХ ДЛЯ ИНТЕНСИФИКАЦИИ ПРОЦЕССА КОММЕРЦИАЛИЗАЦИИ ИННОВАЦИЙ

Аннотация

Статья раскрывает возможности использования систем оперативного анализа в организации и управлении научными и инновационными проектами на предприятиях и в ВУЗах России.

Ключевые слова: оперативный анализ, коммерциализация, управление проектом, информационно-программные ресурсы.

Perevedencev D.A.

Postgraduate student, Izhevsk State Technical University

THE CAPABILITIES SYSTEMS OPERATIONAL ANALYSIS OF DATA FOR  INTENSIFICATION THE PROCESS OF COMMERCIALIZATION INNOVATION

Abstract

The article reveals the possibility using systems operational analysis in the organization and management of research and innovation projects in enterprises and Universities.

Keywords: operational analysis, commercialization, project management, information and software resources.

It must be recognized that the most effective way of development of innovative environment of the scientific institutions is to control not only of the educational process and the conduct of research and development, but also focus on the development of the commercialization of advanced products and services provided in the walls of the university.

To activate the research and development at universities, mechanisms of innovation environment must be based on modern approaches to organization and management [1].

In turn, during the organization and management of research projects as well be taken into account some of their features. Studies show that for success of the innovation project, based on scientific research, important are the following factors: the relevance of the organization's strategy; a clear market orientation; overcome information barriers in the areas of research and development work and marketing; the sufficiency of funds to carry out for carrying out scientific-research and experimental-design works; encouraging creative aspirations of staff; effective project management.

In this context, project management is the art and science of combining and coordinating people, equipment, materials, funding and scheduling of a particular project on time and within budget. To fulfill the goals of project management should be used such methods and models such as matrix organization works, preparation and monitoring of cost estimates, formalized methods of planning and control of work, conflict resolution, risk management, information systems, decision support, and others.

At the same time during the project should be benchmarks: period of certain tasks must comply with planned in the calendar plan, costs of funds corresponds to the planned, the timely preparation of reports.

Since the most sensitive factors that are subject to random influences, is scope and cost of implementation of the project, then the prerequisite of effective management is the account of uncertainty of future revenues and expenses, as well as the timing of the individual phases of the project [2].

To achieve the set goals effectively apply information-analytical systems, which allow you to store, analyze and process large amounts of data and support both directions of data analysis: operational and intellectual.

Operational analysis (OLAP) allows to extract information  of large amount data that is needed a specific person decision-maker on a specific problem to be solved in a short period of operation of information-analytical system.

Data Mining using modern mathematical apparatus (genetic algorithms, neural networks, fuzzy logic) reveals in the dataset non-obvious patterns.

The organizing principle OLAP- cube in this case may look like (Figure 1):

Fig. 1 - The organizing principle of the multidimensional cube

 

In cell 1, for example, located facts relating to the project 5, performed by executing the grant fund RHF, in cell 2 - to the project 3  under the guidance of the scientist 1 commissioned by the Ministry of Education 1, and cell 3 - to the project 3  under leadership the scientist, who is the executor of the project 5, commissioned by a commercial organization.

Also, the use of OLAP technology can effectively solve the problem:

1. The analysis of the scientific activity of the employee, a graduate student or a university student to assess the possibility of integrating the team in the context of a particular project of its publications, experience, participation in other projects, etc .;
2. The preliminary analysis of the capabilities and resources of the university to support the decision to participate in a particular tender, application, etc .;
3. Analysis of existing projects in the context of scientific or commercial appeal for a specific customer, and other fund.

As the analysis to date, OLAP and data mining are used in innovative activities of the university due to its speed, efficiency and clarity. In this regard, the operational analysis of the data is a necessary part of the analytical work of the expert in science and innovation and must find their place in the organization of innovations projects in the modern information society.

Литература

1. Гаина А.А., Кобина Л.А. Развитие инновационной среды вуза [Электронный ресурс] // Международный экономический форум [Офиц. сайт]. URL: http://conference.be5.biz/r2012/3098.htm (дата обращения: 15.08.2014).
2. Кирина Л. В., Астанина Л. А. Моделирование инновационных процессов // Вестник НГУ. Серия Социально – экономические науки. Том 8., выпуск 2. – 2008 г., - С. 103-108

References

1. Gaina A.A., Kobina L.A. Razvitie innovatsionnoi sredy vuza [elektronnyi resurs] // Mezhdunarodnyi ekonomichesky forum [ofits. sait]. URL: http://conference.be5.biz/r2012/3098.htm (data obrashcheniya: 15.08.2014).
2. Kirina L.V., Astanina L.A. Modelirovanie innovatsionnykh protsessov // Vestnik NGU. seriya Sotsialno – ekonomicheskie nauki. tom 8., vypusk 2. – 2008 g., - s. 103-108