scholarly journals Big data analytics of the technological equipment based on Data Lake architecture

2019 ◽  
Vol 298 ◽  
pp. 00079 ◽  
Author(s):  
Ilya Kovalev ◽  
Ramil Nezhmetdinov ◽  
Denis Kvashnin
Keyword(s):  
Data Aggregation ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Traditional Approach ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Industrial Enterprises ◽  
Industrial Companies ◽  
Whole Process ◽  
Almost All

Currently, more and more managers of medium and large industrial companies are thinking about conducting a digital transformation of their enterprise. Each company is forced to strive to find an approach to optimizing production in order to remain competitive in the market. For industrial enterprises, this approach may be a digital transformation using the ideas of Industry 4.0. The digital transformation of an enterprise is a complex and multifaceted process that affects almost all levels of production. At the head of this whole process are data. Data on the work of production must be collected, stored, aggregated, transferred to various levels. Existing methods for storing data are not always suitable for working with BigData, new solutions are needed. The paper shows a comparison of the traditional approach to data aggregation and a promising direction based on the architecture of Data Lake.

Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context

2021 ◽  
Author(s):  
Renan Bonnard ◽  
Márcio Da Silva Arantes ◽  
Rodolfo Lorbieski ◽  
Kléber Magno Maciel Vieira ◽  
Marcelo Canzian Nunes
Keyword(s):  
Big Data ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Advanced Manufacturing

Classification of Pests for Rice Crop Using Big Data Analytics

2019 ◽  
Vol 8 (3) ◽  
pp. 27-31
Author(s):  
R. P. L. Durgabai ◽  
P. Bhargavi ◽  
S. Jyothi
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Andhra Pradesh ◽  
Big Data Analytics ◽  
Rice Crop ◽  
Strategic Decisions ◽  
High Productivity ◽  
Almost All ◽  
Big Data Technology

Data, in today’s world, is essential. The Big Data technology is rising to examine the data to make fast insight and strategic decisions. Big data refers to the facility to assemble and examine the vast amounts of data that is being generated by different departments working directly or indirectly involved in agriculture. Due to lack of resources the pest analysis of rice crop is in poor condition which effects the production. In Andhra Pradesh rice is cultivated in almost all the districts. The goal is to provide better solutions for finding pest attack conditions in all districts using Big Data Analytics and to make better decisions on high productivity of rice crop in Andhra Pradesh.

Big Data Applications in Healthcare

Big Data ◽  
2016 ◽  
pp. 1247-1259 ◽  
Author(s):  
Jayanthi Ranjan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Industry ◽  
Big Data Applications ◽  
Business Functions ◽  
Automated Algorithms ◽  
Almost All ◽  
Tools And Techniques ◽  
Research Centres

Big data is in every industry. It is being utilized in almost all business functions within these industries. Basically, it creates value by converting human decisions into transformed automated algorithms using various tools and techniques. In this chapter, the authors look towards big data analytics from the healthcare perspective. Healthcare involves the whole supply chain of industries from the pharmaceutical companies to the clinical research centres, from the hospitals to individual physicians, and anyone who is involved in the medical arena right from the supplier to the consumer (i.e. the patient). The authors explore the growth of big data analytics in the healthcare industry including its limitations and potential.

Digital Transformation and Industry 4.0

2021 ◽  
pp. 1-17
Author(s):  
Hanaa Abdulraheem Yamani ◽  
Waleed Tageldin Elsigini
Keyword(s):  
Customer Service ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Digital Transformation ◽  
Fourth Industrial Revolution ◽  
Industrial Companies ◽  
The Future ◽  
Information And Communication ◽  
Definition Of

The current era is witnessing many changes on various levels. The information and communication revolutions are considered one of the important changes which has cast a shadow over how different institutions in society work via the phenomenon of digitization. As some of the most important institutions of society, industrial companies have been responding to this phenomenon of digital transformation to improve products and customer service while achieving a significant profitable return. This response by these institutions to the digital transformation has resulted in the emergence of the so-called fourth industrial revolution. In this context, this chapter reviews the definition of digital transformation as well as its dimensions, benefits, and obstacles. It also comments on the future of digital transformation and its relationship with industry. Ultimately it presents the fourth industrial revolution in terms of its definition, history, criteria, benefits, and the challenges it faces moving into the future.

Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0

2022 ◽  
pp. 406-428
Author(s):  
Lejla Banjanović-Mehmedović ◽  
Fahrudin Mehmedović
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Manufacturing Systems ◽  
System Modeling ◽  
Big Data Analytics ◽  
Intelligent Manufacturing ◽  
Intelligent Manufacturing Systems ◽  
Intelligent Decision Making

Intelligent manufacturing plays an important role in Industry 4.0. Key technologies such as artificial intelligence (AI), big data analytics (BDA), the internet of things (IoT), cyber-physical systems (CPSs), and cloud computing enable intelligent manufacturing systems (IMS). Artificial intelligence (AI) plays an essential role in IMS by providing typical features such as learning, reasoning, acting, modeling, intelligent interconnecting, and intelligent decision making. Artificial intelligence's impact on manufacturing is involved in Industry 4.0 through big data analytics, predictive maintenance, data-driven system modeling, control and optimization, human-robot collaboration, and smart machine communication. The recent advances in machine and deep learning algorithms combined with powerful computational hardware have opened new possibilities for technological progress in manufacturing, which led to improving and optimizing any business model.

Artifical Intelligence and CRM

2022 ◽  
pp. 92-114
Author(s):  
Shailja Dixit
Keyword(s):  
Customer Service ◽  
Data Analytics ◽  
Business Models ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Disruptive Technologies ◽  
Artifical Intelligence ◽  
Customer Lifetime ◽  
Customer Care ◽  
Transformation Potential

Disruptive technologies such as IoT, big data analytics, blockchain, and AI have changed the ways businesses operate, with AI holding immense marketing transformation potential. AI is influencing marketing strategies, business models, sales processes, customer service options, and customer behaviors. AI-CRM's improving ability to predict customer lifetime value will generate an inevitable rise in implementing adapted treatment of customers, leading to greater customer prioritization and service discrimination in markets. CSPs are working through the challenging process of digital transformation, driven by the need to compete with fast-moving OTT and consumer tech players. CSPs need to move quickly and can advance digital transformation with solutions that leverage AI which can drive value across the business from network optimization and data analytics through to customer care and marketing engagement. The chapter tries to identify how AI is impacting the CRM in the telecom industry and leveraging the benefits of this technology for better customer management and growth.

scholarly journals Marketing Innovations in Industry 4.0 and Their Impacts on Current Enterprises

2019 ◽  
Vol 9 (18) ◽  
pp. 3685 ◽  
Author(s):  
Otakar Ungerman ◽  
Jaroslava Dědková
Keyword(s):  
Correlation Analysis ◽  
Industry 4.0 ◽  
Marketing Mix ◽  
Descriptive Statistics ◽  
Statistical Hypothesis ◽  
Primary Research ◽  
Strategic Objectives ◽  
Industrial Enterprises ◽  
Industrial Companies ◽  
The Relationship

This paper discussed the marketing innovations associated with Industry 4.0 and the effects that these innovative approaches cause. The main aim of the research was to discover the relationship between marketing innovations and their effects. Knowledge of this relationship can be used for the strategic planning of industrial companies in practice. The research methodology consisted of pilot research followed by primary research in industrial enterprises. The data were evaluated by descriptive statistics, statistical hypothesis, and correlation analysis. Through the research, the authors identified the importance of 17 innovative marketing tools and the strength of the use of 11 effects resulting from the implementation of these tools. The authors identified the relationships between tools and their implications in Industry 4.0 where a correlation was demonstrated. A list of 11 strategic objectives was created and, subsequently, a specific marketing mix proposal for each objective consisting of innovative marketing tools was as well. The results of this work enable enterprises involved in Industry 4.0 to better plan.

scholarly journals Key factors of development of the industrial enterprises in the conditions of the industry 4.0

2018 ◽  
Vol 11 (1) ◽  
pp. 11-19
Author(s):  
T. O. Tolstykh ◽  
L. A. Gamidullayeva ◽  
E. V. Shkarupeta
Keyword(s):  
Public Relations ◽  
Organizational Development ◽  
Industry 4.0 ◽  
Digital Economy ◽  
Digital Products ◽  
Industrial Enterprises ◽  
Industrial Companies ◽  
Digital Ecosystem ◽  
The Future ◽  
Innovative Products

he digital economy actively develops in Russia: according to the report of World Economic Forum, on indicators of availability, use and influence of appropriate technologies on economy and the public relations our country treats 30% of the most advanced countries. The programs of digital economy adopted in the different countries put one of key indicators digitalization of traditional branches. If to speak about manufacturing sectors, then their digitalization is defined substantially by the industrial Internet and depth of his use. Many players – both the industrial companies, and telecommunication are interested in development and introduction of these technologies, and suppliers of the equipment, are created special associations and associations. The purpose of this article is the description of models and algorithms of processes of digitalization of key information (intra-corporate and external) activity of the industrial enterprise; development of methods, technologies and analysis algorithms of «big data» on the basis of technology of the industry 4.0 for management of the industrial enterprises for development of their business. As the frontier of organizational development of processes of digital transformation the organization of the laboratory allowing to carry out the analysis, assessment and engineering of the existing processes at the industrial enterprises from positions of digitalization, productivity, design orientation and efficiency is considered. The analysis of international and Russian experience of creation of similar laboratories within a national innovative digital ecosystem is carried out. The digital laboratory helps to accelerate process of creation of new innovative products and services for growth of business and the successful competition on Russian and the world markets: possibly not only to present, but also to simulate the future of business in 10–20 years: to create prototypes of digital products, to test them, to check as they will work in the future and if necessary to finish.

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