New technologies that change both business and corporate IT require changes in the ITIL process model to conform with Agile and DevOps models. Both fit basic ITIL principles though they follo spiral rather than a cascade model, traditionally described in ITIL documents. Transition to nes models is a natural direction of ITIL development
Today, ITSM is one of the de facto standards of IT management and its importance is undisputable. Meanwhile only a limited number of ITSM processes is implemented and this state of affairs persists in Russia for more than 10 years. There are fundamental reasons, not just lack of maturity of the users. What are these reasons and how to evaluate the necessity of ITSM processes at the preparation stage of the project?
Many different data management systems are available nowadays, ranging from familiar SQL-based solutions to completely new systems designed from scratch. Wide range of available options made it possible to choose one that optimally suits application requirements. However, one can benefit even more from using different solutions within a single application for particular tasks. This paper focuses on collaboration between traditional SQL-based systems and currently popular NoSQL products.
Developed countries are facing an urgent problem of population aging. How can we overcome social and economic consequences of aging processes?
Mobile Ecosystems have been related to products, or to a community of developers around a product and gives the certain advantages to the platform owners and participants of the ecosystem. The paper answers the question -- what are the existing approaches to build mobile ecosystems, who are the participants and what are their benefits?
Today’s data science and business often live apart: IT companies are mired in «burning» projects and do not have enough resources to try out new methods of data analysis. Meanwhile, these new fresh-developed methods are often too crude to be put on stream. Here we present an analytic data processing technology that is based on rough set theory approximations and is shown to be well suited for Big Data analysis.