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The importance of Big Data Analytics technology in business management

Pizło Wojciech, Kulykovets Olena, Prokopowicz Dariusz, Mazurkiewicz-Pizło Anna, Kałowski Adam, Paprocka Małgorzata Wiktoria, Stawicka Ewa, Skarzyńska Edyta

Cybersecurity and Law

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2023

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Vol. 10 (2)

270--282

EN

Data processing, artificial intelligence and IoT technologies are on the rise. The role of data transfer security systems and databases, known as Big Data, is growing. The main cognitive aim of the publication is to identify the specific nature of Big Data management in an enterprise. The paper uses the bibliographic Elsevier and Springer Link databases, and the Scopus abstract database. The distribution of keywords, drawing attention to four main areas related to research directions, is indicated, i.e., Big Data and the related terms „human”, „IoT” and „machine learning”. The paper presents the specific nature of Big Data together with Kitchin and McArdle’s research, indicating the need for a taxonomic ordering of large databases. The precise nature of Big Data management, including the use of advanced analytical techniques enabling managerial decision-making, was identified. The development of Cyber Production Systems (CPS), based on BD, integrating the physical world of an enterprise with the digitisation of information as the concept of Digital Twins (DTs), was also indicated. CPS offer the opportunity to increase enterprise resilience through increased adaptability, robustness and efficiency. With DTs, manufacturing costs are reduced, the product life cycle is shortened, and production quality increases.

PL

W zarządzaniu przedsiębiorstwem na popularności zyskuje m.in. przetwarzanie dużych zbiorów danych, zastosowanie sztucznej inteligencji i technologie IoT. Rośnie rola systemów bezpieczeństwa przesyłania danych oraz baz danych określanych jako Big Data. Głównym celem poznawczym publikacji jest identyfikacja specyfiki zarządzania Big Data w przedsiębiorstwie. W pracy wykorzystano bibliograficzne bazy danych Elsevier i Springer Link oraz bazę abstraktów Scopus. Wskazano rozkład słów kluczowych, zwracając uwagę na główne obszary dotyczące kierunków badań Big Data i związanych z nimi terminów „człowiek”, „IoT” oraz „uczenie maszynowe”. Artykuł przedstawia specyfikę Big Data, wskazuje m.in. badania Kitchina i McArdle’a opisujące potrzebę uporządkowania taksonomicznego dużych baz danych. W artykule zidentyfikowano charakter zarządzania Big Data, w tym wykorzystanie zaawansowanych technik analitycznych umożliwiających podejmowanie decyzji zarządczych. Wskazano również rozwój Cyber Production Systems (CPS), opartych na BD, integrujących fizyczny świat przedsiębiorstwa z digitalizacją informacji jako koncepcję Digital Twins (DTs). CPS oferują możliwość zwiększenia odporności przedsiębiorstwa poprzez zwiększoną zdolność adaptacji, solidność i wydajność. Dzięki DT koszty produkcji są zmniejszone, cykl życia produktu jest skrócony, a jakość produkcji wzrasta.

2

Implementation of Industry 4.0 Techniques in Lean Production Technology: A Literature Review

Lucantoni Laura, Antomarioni Sara, Ciarapica Filippo Emanuele, Bevilacqua Maurizio

Management and Production Engineering Review

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2022

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Vol. 13, No. 3

83--93

EN

Lean thinking and Industry 4.0 have been broadly investigated in recent years in intelligent manufacturing. Lean Production is still one of the most efficient industrial solutions in business and research, despite being implemented for a long time. On the other hand, Industry 4.0 has been introduced referring to the fourth industrial revolution. This study aims to analyze the combination of both Industry 4.0 and Lean production practices through a systematic literature review from a Lean Automation perspective. In this field, 189 articles are examined using VOSviewer for cluster analysis. Then, a more detailed analysis is provided to explore how Industry 4.0 and Lean techniques are integrated from a practical perspective. Results highlighted Big Data Analysis and Value Stream Mapping as the most common techniques, also emphasizing a growing trend toward new publications. Nevertheless, few practical applications are identified in the literature highlighting six gaps in the correlation of LA practices.

3

Big data-driven framework for viral churn prevention: a case study

Lucantoni Laura, Antomarioni Sara, Bevilacqua Maurizio, Ciarapica Filippo E.

Management and Production Engineering Review

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2020

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Vol. 11, No. 3

38--47

EN

The application of churn prevention represents an important step for mobile communication companies aiming at increasing customer loyalty. In a machine learning perspective, Customer Value Management departments require automated methods and processes to create marketing campaigns able to identify the most appropriate churn prevention approach. Moving towards a big data-driven environment, a deeper understanding of data provided by churn processes and client operations is needed. In this context, a procedure aiming at reducing the number of churners by planning a customized marketing campaign is deployed through a data-driven approach. Decision Tree methodology is applied to drow up a list of clients with churn propensity: in this way, customer analysis is detailed, as well as the development of a marketing campaign, integrating the individual churn model with viral churn perspective. The first step of the proposed procedure requires the evaluation of churn probability for each customer, based on the influence of his social links. Then, the customer profiling is performed considering (a) individual variables, (b) variables describing customer-company interactions, (c) external variables. The main contribution of this work is the development of a versatile procedure for viral churn prevention, applying Decision Tree techniques in the telecommunication sector, and integrating a direct campaign from the Customer Value Management marketing department to each customer with significant churn risk. A case study of a mobile communication company is also presented to explain the proposed procedure, as well as to analyze its real performance and results.

4

A Novel System Architecture for an Improved Self-care Solution – Conceptual Design and Key Components

Santos Patrick, Ramos Jorge, Seabra Eduardo, Castro José

Journal of Telecommunications and Information Technology

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2020

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nr 4

88--97

EN

The high penetration rate that mobile devices enjoy in to day’s society has facilitated the creation of new digital services, with those offered by operators and content providers standing out. However, even this has failed to encourage consumers to express positive opinions on telecommunication services, especially when compared with other sectors. One of the main reasons of the mistrust shown is the low level of quality of customer service provided an area that generates high costs for the operators themselves, due to the high number of people employed at call centers in order to handle the volume of calls received. To face these challenges, operators launched self-care applications in order to provide customers with a tool that would allow them to autonomously manage the services they have subscribed. In this paper, we present an architecture that provides customized information to customers – a solution that is separate from mobile operating systems and communication technologies.

5

A Review on Big Data Management and Decision-Making in Smart Grid

Mohamed Amira, Refaat Shady S., Abu-Rub Haitham

Power Electronics and Drives

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2019

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Vol. 4 (39)

1--13

EN

Smart grid (SG) is the solution to solve existing problems of energy security from generation to utilization. Examples of such problems are disruptions in the electric grid and disturbances in the transmission. SG is a premium source of Big Data. The data should be processed to reveal hidden patterns and secret correlations to extrapolate the needed values. Such useful information obtained by the so-called data analytics is an essential element for energy management and control decision towards improving energy security, efficiency, and decreasing costs of energy use. For that reason, different techniques have been developed to process Big Data. This paper presents an overview of these techniques and discusses their advantages and challenges. The contribution of this paper is building a recommender system using different techniques to overcome the most obstacles encountering the Big Data processes in SG. The proposed system achieves the goals of the future SG by (i) analyzing data and executing values as accurately as possible, (ii) helping in decision-making to improve the efficiency of the grid, (iii) reducing cost and time, (iv) managing operating parameters, (v) allowing predicting and preventing equipment failures, and (vi) increasing customer satisfaction. Big Data process enables benefits that were never achieved for the SG application.

6

Towards a different world – on the potential of the internet of everything

Płaza Mirosław, Belka Radosław, Szcześniak Zbigniew

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2019

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T. 9, nr 2

8--11

EN

Internet-based technologies are moving faster and faster into many spheres of our lives and at the same time are a key component of the ongoing technological revolution, which is why there are many ongoing scientific projects aimed at their development. The article presents a discussion on the development of Internet-based technologies known as the Internet of Everything (IoE). The paper presents the areas in which these technologies are most often used. A multi-layered reference model and a procedure for subsequent actions in designing innovative solutions in this area are presented.

PL

Technologie internetowe wkraczają coraz szybciej w liczne sfery naszego życia i jednocześnie stanowią kluczowy komponent trwającej dziś rewolucji technologicznej, dlatego też prowadzonych jest obecnie wiele projektów naukowych ukierunkowanych na ich rozwój. Artykuł przedstawia dyskusję dotyczącą rozwoju technologii internetowych znanych pod nazwą Internetu wszechrzeczy (IoE). W pracy pokazano obszary, w których technologie te znajdują najczęściej zastosowania. Przytoczono wielowarstwowy model referencyjny oraz procedurę kolejnych działań przy projektowaniu nowatorskich rozwiązań w tym zakresie.

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Integracja Big Data i Business Intelligence jako innowacyjne rozwiązanie wspomagające funkcjonowanie nowoczesnych organizacji

Bielak Ł., Muryjas P.

Journal of Computer Sciences Institute

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2016

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Vol. 1

6--13

PL

Celem niniejszego artykułu jest przedstawienie możliwości integracji Business Intelligence(BI) i Big Data (BD). Na podstawie studiów literaturowych określono potencjalne korzyści i wady płynące z takiego rozwiązania. Ponadto, wymienione zostały korzyści jakie odniosły organizacje, które wdrożyły rozwiązania BI i BD. Praca obejmuje także autorski projekt systemu integrującego BI i BD w organizacji z sektora medycznego.

EN

The purpose of this article is to present the possibilities of integration of Business Intelligence (BI) and Big Data (BD). Based on literature studies identified the potential benefits and drawbacks coming from this solution. In addition the benefits of this solution were listed, based on case studies. The article also includes a proprietary system design that integrates BI and BD in the organization of the medical sector.

8

Analityka big data w strategiach rozwoju przedsiębiorstw

Kościelniak H.

Logistyka

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2015

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nr 3

2321--2325, CD 1

PL

Jednym z najważniejszych wyzwań zarządzania strategicznego współczesnych przedsiębiorstw jest analityka wielkich zbiorów danych. Analityka wspiera bezpośrednio operacyjne i strategiczne procesy biznesowe przedsiębiorstw. Umiejętność jak najszybszego wykorzystania znalezionych w wielkich zbiorach danych wartości biznesowych pozwala przedsiębiorstwom budować strategię rozwoju trudną do skopiowania. W artykule wskazano na złożoność i rozległość rozpoznania otoczenia i możliwości przedsiębiorstw, i rolę analityki big data w tym zakresie; podjęto próbę oceny wykorzystania big data w biznesie. Dla badanego przedsiębiorstwa transportowego podano przykłady rozwiązań (decyzji biznesowych) przy wykorzystaniu danych nieuporządkowanych.

EN

One of the most important challenges of strategic management of modern enterprises is analysis of large data sets. The analytics supports the operational and strategic business processes of enterprises directly. The ability is to use business values quickly, which were found in large data sets, that lets enterprises to build a development strategy difficult to copy. The article shows the complexity and extent of the environment and also recognition of opportunities for business, and the role of big data analytics in this regard; there has been made an attempt of the evaluation at using data in the business. For an examined enterprise were given examples of transport solutions (of business decisions) by using unordered data.