Big Data and Simulations for the Solution of Controversies in Small Businesses

2018 ◽  
pp. 6907-6915
Author(s):  
Milena Janakova
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Small Businesses ◽  
Mathematical Methods ◽  
The Road ◽  
True Story ◽  
Variable Level ◽  
Global Information Society ◽  
Definition Of ◽  
Many Sources

The global information society creates data in various formats and data is stored in many sources. Interest is focused on true story formation with respect to sustainable development. The suitable recommendation is to implement a multidimensional view on big data. Such an approach works with big data along three levels. Basic level represents default activities and analyses for data storage in data warehouse. Advanced level is focused on searching for links between stored data and information sources in the global society and variable level searches unexpected events based on complex statistics and mathematical methods with the support of Artificial Intelligence, Business Intelligence, Customer Intelligence, Competitive Intelligence, Swarm Intelligence. These kinds of activities are important for IT product development such as specification of the road for an adopted methodology, definition of a reference for needed dimensions and phases for IT development, and also as a warning against omissions and mistakes.

Big Data and Simulations for the Solution of Controversies in Small Businesses

2019 ◽  
pp. 657-667
Author(s):  
Milena Janakova
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Small Businesses ◽  
Mathematical Methods ◽  
The Road ◽  
True Story ◽  
Variable Level ◽  
Global Information Society ◽  
Definition Of ◽  
Many Sources

The global information society creates data in various formats, and data is stored in many sources. Interest is focused on true story formation with respect to sustainable development. The suitable recommendation is to implement a multidimensional view on big data. Such an approach works with big data on three levels. The basic level represents default activities and analyses for data storage in data warehouse. The advanced level is focused on searching for links between stored data and information sources in the global society, and variable level searches unexpected events based on complex statistics and mathematical methods with the support of artificial intelligence, business intelligence, customer intelligence, competitive intelligence, swarm intelligence. These kinds of activities are important for IT product development such as specification of the road for an adopted methodology, definition of a reference for needed dimensions and phases for IT development, and also as a warning against omissions and mistakes.

On the Road to Ephesus

2015 ◽  
pp. 102-125
Author(s):  
Suzanne Roff-Wexler
Keyword(s):  
Big Data ◽  
Future Research ◽  
Review Of Literature ◽  
Healthcare Organizations ◽  
Research Directions ◽  
The Road ◽  
Future Research Directions ◽  
On The Road ◽  
Definition Of

Following a brief review of literature on big data as well as wisdom, this chapter provides a definition of data-based wisdom in the context of healthcare organizations and their visions. The author addresses barriers and ways to overcome barriers to data-based wisdom. Insights from interviews with leading healthcare professionals add practical meaning to the discussion. Finally, future research directions and questions are suggested, including the role of synchronicity and serendipity in data-based wisdom. In this chapter, developing data-based wisdom systems that flourish Wisdom, Virtue, Intellect, and Knowledge are encouraged.

On the Road to Ephesus

Big Data ◽  
2016 ◽  
pp. 2275-2299
Author(s):  
Suzanne Roff-Wexler
Keyword(s):  
Big Data ◽  
Future Research ◽  
Review Of Literature ◽  
Healthcare Organizations ◽  
Research Directions ◽  
The Road ◽  
Future Research Directions ◽  
On The Road ◽  
Definition Of

Following a brief review of literature on big data as well as wisdom, this chapter provides a definition of data-based wisdom in the context of healthcare organizations and their visions. The author addresses barriers and ways to overcome barriers to data-based wisdom. Insights from interviews with leading healthcare professionals add practical meaning to the discussion. Finally, future research directions and questions are suggested, including the role of synchronicity and serendipity in data-based wisdom. In this chapter, developing data-based wisdom systems that flourish Wisdom, Virtue, Intellect, and Knowledge are encouraged.

scholarly journals THEORETICAL ASPECTS OF DEVELOPING LOGISTICS ACTIVITIES OF TRANSPORT ENTERPRISES

2021 ◽  
pp. 110
Author(s):  
L. VOLYNETS
Keyword(s):  
Big Data ◽  
Material Flow ◽  
Practical Implementation ◽  
Competitive Advantages ◽  
Mathematical Methods ◽  
Transport Services ◽  
Definition Of ◽  
Logistics Activity ◽  
The Internet Of Things

The need for improvement and development of logistics activities at transport enterprises is determined. The content of the concept of “logistics activity” and theoretical aspects of its development at transport enterprises are revealed. Complex logistics functions and elementary logistics operations are analyzed. The role and place of logistics activity and its influence on the functioning of transport enterprises are substantiated. The efficiency of logistics activity at transport enterprises and directions of its improvement are analyzed. Among the areas identified there are three main: the use of big data (Big Data), cloud logistics and logistics platforms of supply chains, the Internet of Things. Therefore, the availability and use of information platforms and technologies are extremely important in improving the logistics activities of transport companies. With their appearance, it becomes possible to develop various mathematical methods for simplifying logistics tasks and their practical implementation. It is proved that the use of logistics contributes to the achievement of certain competitive advantages by transport enterprises. The opinions of various authors on the definition of the concept of “logistics activities” are considered and a comprehensive definition of the concept is proposed. The system of management of logistic activity of the enterprise, the place and role of the elements of logistic activity is given and it is proved that performance of tasks of logistic activity at each stage of a material flow management raises the competitiveness of the enterprise in the market of transport services.

scholarly journals Big data life cycle: security issues, challenges, threat and security model

2017 ◽  
Vol 7 (1.3) ◽  
pp. 100
Author(s):  
Bhima SankaramAlladi ◽  
Dr Srinivas Prasad
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Vital Role ◽  
Security Model ◽  
Data Generation ◽  
Security Issues ◽  
Data Preservation ◽  
Data Life Cycle ◽  
Conventional Technology ◽  
Definition Of

Today the technologies of big data are completely bringing a vast change in the entire conventional technology discipline and it’s successfully applying the required latest security design methods to state the upcoming security provocations. Big Data Architecture is a “Data” centric architecture in which security can be included in all the levels. Data is collected from different sources and Data generation is done, the next step it undergoes is Data Processing, the next step is Data storage and the last step is Data analysis. At all the levels Data plays a vital role. It aims to give basic investigation regarding most of the security risks and Big Data provocation and bought out new provocations, complication to the conventional protective domains and also for conventional trends. This deals with the definition of big data and the characteristics that effect most of the data preservation, such as 3V’s, dynamicity. It analyses the original changes and new challenges to Data security. It also provides pitch for real time practice of security infrastructure peripherals which allows extend trusted non-local virtualized processing environment. This research focus on all levels of Big Data where and when the security services and techniques can be included to acquire accurate results.

Data Lake Architecture

2020 ◽  
Vol 10 (1) ◽  
pp. 63-75
Author(s):  
Arvind Panwar ◽  
Vishal Bhatnagar
Keyword(s):  
Big Data ◽  
Data Storage ◽  
World Economy ◽  
Big Data Analytics ◽  
Data Repository ◽  
Market Demand ◽  
Data Warehouses ◽  
The Past ◽  
Many Sources ◽  
Big Data Storage

Data is the biggest asset after people for businesses, and it is a new driver of the world economy. The volume of data that enterprises gather every day is growing rapidly. This kind of rapid growth of data in terms of volume, variety, and velocity is known as Big Data. Big Data is a challenge for enterprises, and the biggest challenge is how to store Big Data. In the past and some organizations currently, data warehouses are used to store Big Data. Enterprise data warehouses work on the concept of schema-on-write but Big Data analytics want data storage which works on the schema-on-read concept. To fulfill market demand, researchers are working on a new data repository system for Big Data storage known as a data lake. The data lake is defined as a data landing area for raw data from many sources. There is some confusion and questions which must be answered about data lakes. The objective of this article is to reduce the confusion and address some question about data lakes with the help of architecture.

High-tech business in crisis conditions: development trends of large, medium and small enterprises

2020 ◽  
Vol 18 (4) ◽  
pp. 48-58
Author(s):  
Vladislav V. Spitsyn ◽  
Alexander A. Mikhal'chuk ◽  
Anastasia A. Bulykina ◽  
Svetlana N. Popova ◽  
Irina E. Nikulina
Keyword(s):  
Small Businesses ◽  
Negative Impact ◽  
Service Industries ◽  
High Tech ◽  
Small Enterprises ◽  
Mathematical Methods ◽  
Crisis Period ◽  
Knowledge Intensive ◽  
Crisis Conditions ◽  
Medium And Small Enterprises

Leading world countries view innovative development and high-tech business as an opportunity to overcome economic stagnation and decline in economic growth. One of the modern trends in the analysis of high-tech development is the study of high-tech knowledge-intensive service industries and their development in times of crisis. The purpose of the paper is to identify patterns of development of large, medium and small enterprises in high-tech service industries in Russia during periods of crisis. Economic and economic-mathematical methods of analysis are applied to the formed samples of enterprises. The research period is 2013-2017. The financial indicators of enterprises were adjusted for the level of accumulated inflation in relation to 2013. According to results, large and medium-sized enterprises showed insignificant or weak significant positive dynamics of revenue during all years of the crisis period. The crisis period did not lead to a decrease in the revenue of these groups of enterprises. The acute phase of the crisis (2014-2015) had a pronounced negative impact on the group of small enterprises in all studied industries, but they successfully recovered in 2016-2017 and reached the pre-crisis level of revenue. The total revenue by industries and groups of enterprises in 2017 became higher than in 2013, and its growth rates were significant for many groups of enterprises, which indicates a successful overcoming of the crisis period and signs of growth in high-tech service industries. Our study shows the need for state support for small businesses in high-tech service industries in crisis conditions, and identifies the possibilities of adaptation of enterprises in these industries to an unfavorable external environment. Our results may be useful for the purposes of government stimulation of economic development in the current environment.

The methodology of experimental research of the feed components extrusion process in order to improve its energy performance

2020 ◽  
pp. 147-152
Author(s):  
E. M. Ratnikov ◽  
D. O. Milko
Keyword(s):  
Experimental Studies ◽  
Energy Performance ◽  
Extrusion Process ◽  
Mathematical Methods ◽  
Screw Extruder ◽  
Mathematical Planning ◽  
Factors Affecting ◽  
Extrusion Processing ◽  
Definition Of

Annotation Purpose. Development of a program and methods for conducting experimental studies of the extrusion process with the definition of parameters and modes of operation of the extruder to improve its energy performance. Methods. Methods of mathematical statistics, synthesis, analysis, description and modeling were used. Results. The application of mathematical methods, in particular mathematical planning, reduces the number of experiments several times, and allows to evaluate the role of influencing factors, obtain a mathematical model of the process and determine the optimal conditions for its parameters and modes, etc. Conclusions. The methodology for experimental studies of a screw extruder is presented with the necessary equipment and methodology for processing the obtained experimental data. A mathematical method of planning, which reduces the number of experiments several times, allows us to evaluate the role of factors affecting productivity and energy intensity is presented. Keywords: extruder, auger, nutrients, research methodology, extrusion, processing, feed.

scholarly journals Big Data Analytics in urology: the story so far and the road ahead

2021 ◽  
Vol 13 ◽  
pp. 175628722199813
Author(s):  
B. M. Zeeshan Hameed ◽  
Aiswarya V. L. S. Dhavileswarapu ◽  
Nithesh Naik ◽  
Hadis Karimi ◽  
Padmaraj Hegde ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Early Stage ◽  
Big Data Analytics ◽  
Positive Trend ◽  
The Road ◽  
Healthcare Data ◽  
Urological Disorders ◽  
Different Sources

Artificial intelligence (AI) has a proven record of application in the field of medicine and is used in various urological conditions such as oncology, urolithiasis, paediatric urology, urogynaecology, infertility and reconstruction. Data is the driving force of AI and the past decades have undoubtedly witnessed an upsurge in healthcare data. Urology is a specialty that has always been at the forefront of innovation and research and has rapidly embraced technologies to improve patient outcomes and experience. Advancements made in Big Data Analytics raised the expectations about the future of urology. This review aims to investigate the role of big data and its blend with AI for trends and use in urology. We explore the different sources of big data in urology and explicate their current and future applications. A positive trend has been exhibited by the advent and implementation of AI in urology with data available from several databases. The extensive use of big data for the diagnosis and treatment of urological disorders is still in its early stage and under validation. In future however, big data will no doubt play a major role in the management of urological conditions.

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