Wyniki wyszukiwania - Biblioteka Nauki

1

The potential benefits of Business Analytics in the sector of financial services

100%

Kulakova Y.

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2015

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nr 7

32-40

EN

Modern digital world has raised many obstacles along with advantages for business processes. Data generated by humanity every day is called now as Big Data, thanks to enormous amount and complexity of types. In today's reality of vast amounts of various types of data, it is important for enterprises to be able to deal with it in a most effective way. For financial services providers, decisions which are based on data rather than intuition can lead to many business benefits such as increasing awareness, boosting customer loyalty, diminishing fraudulence and gaining competitive advantage. Business analytics as complex process of data utilization can help financial services providers to address many challenges and reveal previously unknown insights. Rapid development of IT and consumerization of Internet can facilitate business processes as never before. Cost, complexity and availability of new technologies are playing crucial role in modern business world. In our days, business analytics techniques become more and more affordable even for small or middle size enterprises. Thus, contemporary analytics tools are deserve to be a key element of management process

2

The social and ethical challenges connected with the Big Data phenomenon

86%

Wielki J.

|

tom Vol. 11, No. 2

192--202

EN

The goal of this paper is to analyze the socio-ethical challenges connected with utilization of the Big Data phenomenon by organizations. It is composed of five parts. The first part contains a brief overview of the situation related to the ever increasing amounts of data in the contemporary socio-economic sphere. The next is focused on the Big Data phenomenon and the significant sources behind the growth in data. The following part is devoted to an analysis of the opportunities and benefits connected with the utilization of Big Data. The fourth part focuses on the most significant obstacles and challenges connected with Big Data, with special attention paid to social and ethical issues. The final part of the paper contains the most significant conclusions and suggestions.

PL

Celem niniejszego artykułu jest analiza wyzwań społeczno-etycznych związanych z wykorzystaniem zjawiska Big Data przez organizacje. Składa się on z pięciu części. Pierwsza z nich zawiera krótki przegląd sytuacji związanej z gwałtownym przyrostem ilości danych w sferze społeczno-ekonomicznej. Kolejna koncentruje się na zjawisku Big Data i najważniejszych źródłach przyrostu danych. Następna część poświęcona jest analizie możliwości i korzyści związanych z wykorzystaniem Big Data. Czwarta część artykułu koncentruje się na kluczowych wyzwaniach i przeszkodach związanych z praktycznym wykorzystaniem Big Data, ze szczególnym uwzględnieniem kwestii społeczno-etycznych. Przedstawiona jest w niej również analiza rozwiązań obecnie stosowanych w tej sferze przez organizacje. Ostatnia część artykułu zawiera najważniejsze konkluzje i sugestie.

3

Big data w marketingu - narzędzie doskonalenia relacji z klientami

72%

Wieczorkowski J. , Chomiak-Orsa I. , Pawełoszek I.

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nr 1

3-9

EN

One of the fundamental aspects of the big data phenomenon is the possibility of application in management. This potential differs depending on the specifics of the organization and the area of application. The article aims to indicate the specificity and directions of applying big data methods in marketing, with particular emphasis on improving customer relationships. After presenting the general characteristics of the big data phenomenon in management, the evolution of business analytics related to new possibilities of mass data processing was described. Then, the focus was on the examples of big data applications in improving customer relationships, which confirms the thesis that these methods are very useful in marketing.

PL

Jednym z podstawowych aspektów zjawiska big data, czyli przetwarzania masowych danych, są możliwości zastosowań jego technik w zarządzaniu. Ich potencjał różni się wyraźnie w zależności od specyfiki organizacji i obszaru jej działalności. Celem artykułu jest wskazanie specyfiki i kierunków zastosowań metod big data w zakresie marketingu, ze szczególnym uwzględnieniem doskonalenia relacji z klientami. W artykule przedstawiono ogólną charakterystykę zjawiska big data w kontekście zarządzania, opisano ewolucję analityki biznesowej związaną z nowymi możliwościami przetwarzania masowych danych oraz wskazano przykładowe obszary zastosowań big data w zakresie doskonalenia relacji z klientami, które potwierdzają tezę o wysokiej przydatności tych metod w marketingu.

4

Business analytics of enterprises in terms of strategy

72%

Kościelniak H. , Łęgowik-Świącik S. , Jancikova E.

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tom Vol. 16, No. 1

67--77

EN

The paper is devoted to the problem of strategic business analytics. The aim of the study is to show business analytics supporting the construction and development of the company development strategy. In order to achieve the assumed goal there has been applied the method of critical analysis of the domestic and foreign literature in the field of business analytics of enterprises domestically and worldwide. In the paper, there have been identified the factors for the use of business analytics. Three priority factors which are the arguments for the application of business analytics in management processes and enterprise development strategies are: speed/ease of deployment (68% of indications), ease of use for business users (65% of indications) and self-service and data discovery tools (61% of indications). Moreover, managers of enterprises with the best economic and financial results, achieving return on assets (ROA) of more than 10%, almost agreeably (90% of indications) claim that analytical tools are necessary for the proper implementation of the strategy and the achievement of increasingly higher economic and financial results. The value of the paper consists in showing a new trend in the development of business analytics, which is to support the process of strategic management and analytical competition.

PL

Artykuł poświęcono problematyce strategicznej analityce biznesowej. Celem opracowania jest ukazanie roli analityki biznesowej wspomagającej budowę i realizację strategii rozwoju przedsiębiorstwa. Aby osiągnąć założony cel zastosowano metodę krytycznej analizy literatury krajowej i zagranicznej z zakresu analityki biznesowej oraz przedstawiono badania empiryczne z zakresu stosowania analityki biznesowej przedsiębiorstw na świecie i w kraju. W artykule zidentyfikowano czynniki przemawiające za stosowaniem analityki biznesowej. Trzy priorytetowe czynniki, które przemawiają za stosowaniem analityki biznesowej w procesach zarządzania i strategiach rozwoju przedsiębiorstw to: szybkość i łatwość wdrożenia (68% wskazań), łatwość obsługi przez użytkowników biznesowych (65% wskazań), samoobsługa i wykrywanie danych (61% wskazań). Co więcej, menedżerowie przedsiębiorstw o najlepszych wynikach ekonomiczno-finansowych, osiągających stopę zwrotu kapitału całkowitego (ROA) wyższą niż 10%, prawie zgodnie (90% wskazań) twierdzą, że narzędzia analityczne są niezbędne do właściwej realizacji strategii i osiągania coraz wyższych wyników ekonomiczno-finansowych. Wartość artykułu polega na ukazaniu nowej tendencji w rozwoju analityki biznesowej, jaką jest wspomaganie procesu zarządzania strategicznego i konkurencji analitycznej.

5

The basis of prospective analytics in business

72%

Wolniak R. , Grebski W.

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tom z. 176

771--789

EN

Purpose: The goal of the paper is to analyze the main features, benefits and problems with the prospective analytics usage. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: Prescriptive analytics aims to assist businesses in making informed decisions that optimize desired outcomes or minimize undesired ones. It goes beyond predicting future outcomes and provides recommendations on the best actions to achieve desired goals while considering potential risks and uncertainties. Prescriptive analytics finds applications in various domains such as supply chain management, financial planning, healthcare, marketing, and operations management. It empowers businesses to make data-driven decisions, optimize resource allocation, enhance efficiency, and gain a competitive advantage. Considered the highest level of analytics, prescriptive analytics combines historical data, real-time information, optimization techniques, and decision models to generate actionable recommendations. Originality/value: Detailed analysis of all subjects related to the problems connected with the prospective analytics.

6

Ocena wiedzy współczesnych menedżerów w zakresie narzędzi klasy business intelligence

72%

WAWER M. , MURYJAS P.

|

tom 9

|

nr 4

315-320

PL

Współczesny menedżer powinien stale zdobywać nowe kompetencje wynikające z rozwoju technologii wspierających zarządzanie przedsiębiorstwem. Taką koncepcją, coraz częściej wykorzystywaną w firmach, jest business intelligence (BI). Celem artykułu jest analiza wiedzy menedżerów dotyczącej istoty i narzędzi BI. W jego pierwszej części omówiono podejście zarządzania przez dane oraz ideę BI. Następnie opisano metodykę przeprowadzonego badania ankietowego. Końcową część rozważań stanowi analiza otrzymanych rezultatów wskazujących na niski poziom wiedzy menedżerów o istocie i narzędziach BI.

EN

A contemporary manager should constantly acquire new competences resulting from the development of technologies supporting management the enterprise. Such a concept that is increasingly utilised in companies is business intelligence (BI).The aim of the paper is the analysis of managers’ knowledge of the essence and tools of BI. At the beginning of the article the concept of data driven management and BI has been discussed. Next, the methodology of the questionnaire survey has been described. The final part of the considerations is the analysis of the survey results, which indicate that the level of knowledge of managers about the essence and tools of BI is very low.

7

Functioning of real-time analytics in business

72%

Wolniak R.

|

2023

|

tom z. 172

659--677

EN

Purpose: The goal of the paper is to analyze the main features, benefits and problems with the real-time analytics usage. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The paper focus on the advantages and disadvantages of real-time analytics. The ability to process and analyze data in real-time allows organizations to quickly identify trends and patterns, optimize their operations, and allocate resources more efficiently. Additionally, real-time analytics helps businesses identify new revenue opportunities and optimize their pricing strategies, monitor user behavior, detect security threats, and react without delay. However, real-time analytics can be expensive to implement, require technical expertise, and generate false positives. Proper data quality, security measures, and system scaling are also essential for effective implementation. The vague definition of real-time and the requirement to collect detailed requirements from all stakeholders can also present challenges to businesses. Originality/value: Detailed analysis of all subjects related to the problems connected with the real-time analytics.

8

Wykorzystanie systemów Data Discovery w zarządzaniu w organizacjach not-for-profit

72%

Palonka J.

|

nr 2

EN

Under existing circumstances organizations are forced to efficiently use data in decision-making processes in management. Data Discovery (DD) systems are tools that support business analytics. These are self-service IT tools which can be used by employees lacking specialized IT knowledge. The aim of this paper is to present the possibility of using DD systems in the management of not-for-profit organizations, based on the case study of Volunteer Fire Department in Zabrodzie.

PL

Współczesne warunki funkcjonowania zmuszają organizacje do efektywnego wykorzystywania danych w procesach podejmowania decyzji w zarządzaniu. Systemy Data Discovery (DD) są narzędziami wspomagającymi analitykę biznesową i są przeznaczone do samodzielnego wykorzystywania przez pracowników, którzy nie posiadają specjalistycznej wiedzy informatycznej. Celem artykułu jest zaprezentowanie możliwości wykorzystania systemów DD w zarządzaniu organizacjami not-for-profit na przykładzie Ochotniczej Straży Pożarnej w Zabrodziu.

9

The application of Business Intelligence systems in logistics. review of selected practical examples

58%

Grabińska A. , Ziora L.

|

tom Vol. 1, nr 1

1028--1035

EN

The goal of the paper is to present the application of Business Intelligence systems belonging to the area of business analytics in the domain of logistics and particularly indicate its role and meaning in supporting logistics decision making processes. Its content embraces the characteristic of BI systems, its functionality, construction and benefits resulting from its implementation. The paper also presents review of research and case studies connected to the BI usage in such areas of logistics as optimization of supply chain, managerial dashboard design and improvement of business processes.

10

Analyzing customer behavior – employing business analytics within Industry 4.0 ecosystems

58%

Wolniak R.

|

2024

|

tom z. 195

631--646

EN

Purpose: The purpose of this publication is to present the applications of usage of business analytics in customer behaviour analysis. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The integration of business analytics with customer behavior analysis in Industry 4.0 environments offers businesses a transformative opportunity to gain profound insights into customer preferences, trends, and behaviors. Through the utilization of state-of-the-art technologies and data-driven methodologies, organizations can attain unprecedented levels of precision and detail in understanding customer behavior. Real-time data collection and analysis facilitate agile responses to evolving market dynamics, enabling personalized customer experiences across various channels. Additionally, advanced analytics tools such as predictive modeling and sentiment analysis empower businesses to forecast future trends, address churn, and enhance customer satisfaction. However, businesses may encounter challenges like data quality issues, privacy concerns, and resource limitations. Overcoming these obstacles necessitates a comprehensive approach, involving investments in data governance, talent acquisition, and technology infrastructure. By surmounting these challenges, businesses can harness the full potential of business analytics to drive strategic decisions, refine marketing strategies, and elevate overall business performance within Industry 4.0 environments. Originality/Value: Detailed analysis of all subjects related to the problems connected with the usage of business analytics in the case of smart manufacturing.

11

Smart manufacturing – the utilization of business analytics in Industry 4.0 environments

58%

Wolniak R.

|

2024

|

tom z. 195

647--663

EN

Purpose: The purpose of this publication is to present the applications of usage of business analytics in smart manufacturing. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The integration of business analytics in smart manufacturing within the framework of Industry 4.0 marks a significant stride in industrial processes, offering manifold advantages alongside notable challenges. Throughout this study, we delve into the expansive realm of business analytics applications, encompassing predictive maintenance, quality control, supply chain optimization, and real-time decision-making. Leveraging business analytics yields palpable benefits in smart manufacturing, exemplified by proactive equipment maintenance, stringent quality standards adherence, and streamlined supply chain operations. Additionally, analytics-driven enhancements in production optimization, energy management, demand forecasting, and asset performance management contribute to heightened productivity, cost reduction, and sustainability improvement. Challenges including data integration complexities, implementation intricacies, security concerns, scalability limitations, model interpretability issues, and skill gaps necessitate concerted efforts for effective resolution. Collaboration among stakeholders- manufacturers, software developers, policymakers, and educational institutions—is imperative. Joint initiatives aimed at bolstering data integration capabilities, providing specialized training, fortifying cybersecurity measures, and fostering a culture of continuous improvement are crucial for successful business analytics deployment. Originality/Value: Detailed analysis of all subjects related to the problems connected with the usage of business analytics in the case of smart manufacturing.