Science topic
Business Intelligence - Science topic
Reporting, OLAP, Data Mining, Adaptive Decision Support, Tools
Questions related to Business Intelligence
To what extent can computing and/or data processing power be increased through the use of quantum computers, and what applications of quantum computers are already being developed?
What could be the applications of quantum computers in the future, if the technology of quantum cryptography and other technologies necessary for building quantum computers would be sufficiently improved, would become widespread, their prices would fall, they would become financially accessible not only to the largest corporations and organizations, research and development institutions with large financial capitals enabling the development and implementation of quantum computer technology?
The key technology enabling the construction of quantum computers is quantum cryptography. The technology is expensive and available only to the largest corporations and organizations, research and development institutions with large financial capitals enabling the development and implementation of quantum computer technology. The applications of quantum computers are various. Probably, many companies and businesses in various sectors of the economy, which already use various Industry 4.0/5.0 technologies, including cloud computing of large sets of data and information, use analytics based on integrated information systems using Big Data Analytics and/or Business Intelligence, Internet of Things technologies, Blockchain, machine learning, deep learning, generative artificial intelligence, digital twins, etc. would be interested in applying quantum computer technology to their business, to improve it, to improve their computerized management systems, if the price of this technology dropped significantly. The price drop factor is an important determinant of the spread of the implementation of this technology to many companies, enterprises operating in the SME sector, which do not have large financial budgets for the implementation of development and implementation projects involving the implementation of the latest highly advanced digital technologies, etc., into their business activities. At present, such technologies are developed in a small number of research and development centers, research laboratories run by scientific institutes of universities or large technology companies with large financial funds to allocate to such development and implementation projects.
The use of quantum computers makes it possible, among other things, to create microscopes that image very small objects, such as cell fragments, with the ability to view them live in real time. Currently, such observations are made with electron microscopes, with which, for example, cell organelles are observed but frozen cells rather than live, i.e. biologically functioning cells in real time. A typical feature of quantum computers is that quantum software is not written in Java-type programming languages, but the computer systems used in quantum computers rely on quantum circuit design. The results of research in cosmology, astrophysics, theories on the functioning of key cosmic objects in the Universe are concerned with black holes found in space, for example. However, has anyone seen a black hole realistically up close, no one. Of course, by writing these words, I do not intend to undermine any theories about black holes functioning in space. The point is that quanta can be measured only the necessary research infrastructure is needed. The necessary research infrastructure is expensive and therefore available only to some research, development and implementation centers located in a few research institutes of universities and some large technology companies. The quantum technology necessary to build quantum computers can be developed in various ways. Rather, ions, vortices of currents in superconductors will be controlled by photons, so it makes sense to develop quantum technology based on photons. Any kind of microparticles that can be controlled, changed in some respect, intentionally change their form can be used to build quantum computers. With quantum computers, it will be possible to solve complex, multifaceted problems in which large amounts of data are processed. Therefore, when this technology becomes widespread, its price will be significantly reduced then perhaps in the future the world will move to quantum cryptography. The largest financial investments in the development of quantum technology are made in developed countries where large subsidies from the state's public finance system are allocated for R&D purposes, i.e. primarily in the US, China and Europe. A common feature of the various types of applications of quantum computers is that these computers would enable the processing of much larger volumes of data and information in a relatively short period of time within the framework of multi-criteria, advanced data processing carried out on computerized Big Data Analytics platforms and with the involvement also of other technologies typical of Industry 4.0/5.0. Greater capabilities for advanced, multi-criteria processing of large sets of data and information will allow the solution of complex analytical problems concerning various spheres of human activity and various issues operating in various industries and sectors of the economy.
I described the applications of Big Data technology in sentiment analysis, business analytics and risk management in an article of my co-authorship:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
I invite you to familiarize yourself with the problems described in the article given above and to scientific cooperation in this field.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
What could be the applications of quantum computers in the future, if the technology of quantum cryptography and other technologies necessary for building quantum computers were adequately improved, would become widespread, their prices would fall, they would become financially accessible not only to the largest corporations and organizations, research and development institutions with large financial capitals to enable the development and implementation of quantum computer technology?
To what extent can computing and/or data processing capacities be increased through the use of quantum computers, and what are the already developed applications of quantum computers?
What are the currently developed applications of quantum computers and what might they be in the future?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

How does leadership affect business intelligence adoption
Can the application of generative artificial intelligence technology and Big Data Analytics improve the processes of predictive analytics performed as part of Business Intelligence?
Can the application of generative artificial intelligence technology and Big Data Analytics improve the processes of predictive analytics carried out within the framework of Business Intelligence and thus the effectiveness of business, economic and financial analytics supporting the management process of an organization, enterprise, company, corporation, etc., can be increased? And if so, how and to what extent?
As information systems that allow the largely automated performance of Business Intelligence analytics become an important factor in supporting the process of business management, so the importance of the new technologies of Industry 4.0/5.0, including generative artificial intelligence and Big Data Analytics, to improve the said analytical processes is growing. On the one hand, the obvious point is that the application of generative artificial intelligence technology and Big Data Analytics can improve the processes of predictive analytics carried out within the framework of Business Intelligence, and thus the effectiveness of business, economic and financial analytics supporting the management process of an organization, enterprise, company, corporation, etc. can be increased. However, on the other hand, it is also important to precisely define the determinants that determine the performance of such analytical processes, to point out the role of the new technologies of Industry 4.0/5.0, including generative artificial intelligence and Big Data Analytics technologies in the processes of predictive analytics carried out within the framework of Business Intelligence, and to estimate the extent of the influence of these technologies on the improvement of the said analytical processes.
I am conducting research on this issue. I have included the conclusions of my research in the following article:
Business Intelligence analytics based on the processing of large sets of information with the use of sentiment analysis and Big Data
I invite you to familiarize yourself with the problems described in the publications given above and to cooperate with me in scientific research on these problems.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Can the application of generative artificial intelligence technology and Big Data Analytics improve the processes of predictive analytics carried out within the framework of Business Intelligence and thus the effectiveness of business, economic and financial analytics supporting the management process of an organization, enterprise, company, corporation, etc., can be increased? And if so, how and to what extent?
Can the use of generative artificial intelligence and Big Data Analytics technologies improve the processes of predictive analytics performed as part of Business Intelligence?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

The application of business intelligence (BI) in unemployment insurance significantly transforms decision-making processes and operational efficiency by enabling data-driven insights that improve both strategic and operational outcomes. BI tools aggregate and analyze large volumes of data from diverse sources, allowing policymakers and administrators to make informed decisions that align with current economic conditions, labor market trends, and claimant needs. This data-driven approach helps in accurately assessing claim validity, identifying fraudulent claims, predicting future trends, and improving resource allocation.
My research title is Enhancing Business Intelligence: Leveraging Big Data Analytics and Machine Learning in ERP Systems for Strategic Decision Making for Logistic Businesses.
I would like to ask fellow researchers to share some insights on what research methodology I can or should use for my particular topic.
How to build a sustainable data center based on Big Data Analytics, AI, BI and other Industry 4.0/5.0 technologies and powered by renewable and carbon-free energy sources?
If a Big Data Analytics data center is equipped with advanced generative artificial intelligence technology and is powered by renewable and carbon-free energy sources, can it be referred to as sustainable, pro-climate, pro-environment, green, etc.?
Advanced analytical systems, including complex forecasting models that enable multi-criteria, highly sophisticated, big data and information processing-based forecasts of the development of multi-faceted climatic, natural, social, economic and other processes are increasingly based on new Industry 4.0/5.0 technologies, including Big Data Analytics and machine learning, deep learning and generative artificial intelligence. The use of generative artificial intelligence technologies enables the application of complex data processing algorithms according to precisely defined assumptions and human-defined factors. The use of computerized, integrated business intelligence information systems allows real-time analysis on the basis of continuously updated data provided and the generation of reports, reports, expert opinions in accordance with the defined formulas for such studies. The use of digital twin technology allows computers to build simulations of complex, multi-faceted, prognosticated processes in accordance with defined scenarios of the potential possibility of these processes occurring in the future. In this regard, it is also important to determine the probability of occurrence in the future of several different defined and characterized scenarios of developments, specific processes, phenomena, etc. In this regard, Business Intelligence analytics should also make it possible to precisely determine the level of probability of the occurrence of a certain phenomenon, the operation of a process, the appearance of described effects, including those classified as opportunities and threats to the future development of the situation. Besides, Business Intelligence analytics should enable precise quantitative estimation of the scale of influence of positive and negative effects of the operation of certain processes, as well as factors acting on these processes and determinants conditioning the realization of certain scenarios of situation development. Cloud computing makes it possible, on the one hand, to update the database with new data and information from various institutions, think tanks, research institutes, companies and enterprises operating within a selected sector or industry of the economy, and, on the other hand, to enable simultaneous use of a database updated in this way by many beneficiaries, many business entities and/or, for example, also by many Internet users in a situation where the said database would be made available on the Internet. In a situation where Internet of Things technology is applied, it would be possible to access the said database from the level of various types of devices equipped with Internet access. The application of Blockchain technology makes it possible to increase the scale of cybersecurity of the transfer of data sent to the database and Big Data information as part of the updating of the collected data and as part of the use of the analytical system thus built by external entities. The use of machine learning and/or deep learning technologies in conjunction with artificial neural networks makes it possible to train an AI-based system to perform multi-criteria analysis, build multi-criteria simulation models, etc. in the way a human would. In order for such complex analytical systems that process large amounts of data and information to work efficiently it is a good solution to use state-of-the-art super quantum computers characterized by high computing power to process huge amounts of data in a short time. A center for multi-criteria analysis of large data sets built in this way can occupy quite a large floor space equipped with many servers. Due to the necessary cooling and ventilation system and security considerations, this kind of server room can be built underground. while due to the large amounts of electricity absorbed by this kind of big data analytics center, it is a good solution to build a power plant nearby to supply power to the said data center. If this kind of data analytics center is to be described as sustainable, in line with the trends of sustainable development and green transformation of the economy, so the power plant powering the data analytics center should generate electricity from renewable energy sources, e.g. from photovoltaic panels, windmills and/or other renewable and emission-free energy sources of such a situation, i.e., when a data analytics center that processes multi-criteria Big Data and Big Data Analytics information is powered by renewable and emission-free energy sources then it can be described as sustainable, pro-climate, pro-environment, green, etc. Besides, when the Big Data Analytics analytics center is equipped with advanced generative artificial intelligence technology and is powered by renewable and emission-free energy sources then the AI technology used can also be described as sustainable, pro-climate, pro-environment, green, etc. On the other hand, the Big Data Analytics center can be used to conduct multi-criteria analysis and build multi-faceted simulations of complex climatic, natural, economic, social processes, etc. with the aim of, for example. to develop scenarios of future development of processes observed up to now, to create simulations of continuation in the future of diagnosed historical trends, to develop different variants of scenarios of situation development according to the occurrence of certain determinants, to determine the probability of occurrence of said determinants, to estimate the scale of influence of external factors, the scale of potential materialization of certain categories of risk, the possibility of the occurrence of certain opportunities and threats, estimation of the level of probability of materialization of the various variants of scenarios, in which the potential continuation of the diagnosed trends was characterized for the processes under study, including the processes of sustainable development, green transformation of the economy, implementation of sustainable development goals, etc. Accordingly, the data analytical center built in this way can, on the one hand, be described as sustainable, since it is powered by renewable and emission-free energy sources. In addition to this, the data analytical center can also be helpful in building simulations of complex multi-criteria processes, including the continuation of certain trends of determinants influencing the said processes and the factors co-creating them, which concern the potential development of sustainable processes, e.g. economic, i.e. concerning sustainable economic development. Therefore, the data analytical center built in this way can be helpful, for example, in developing a complex, multifactor simulation of the progressive global warming process in subsequent years, the occurrence in the future of the negative effects of the deepening scale of climate change, the negative impact of these processes on the economy, but also to forecast and develop simulations of the future process of carrying out a pro-environmental and pro-climate transformation of the classic growth, brown, linear economy of excess to a sustainable, green, zero-carbon zero-growth and closed-loop economy. So, the sustainable data analytical center built in this way will be able to be defined as sustainable due to the supply of renewable and zero-carbon energy sources, but will also be helpful in developing simulations of future processes of green transformation of the economy carried out according to certain assumptions, defined determinants, estimated probability of occurrence of certain impact factors and conditions, etc. orz estimating costs, gains and losses, opportunities and threats, identifying risk factors, particular categories of risks and estimating the feasibility of the defined scenarios of the green transformation of the economy planned to be implemented. In this way, a sustainable data analytical center can also be of great help in the smooth and rapid implementation of the green transformation of the economy.
Kluczowe kwestie dotyczące problematyki zielonej transformacji gospodarki opisałem w poniższym artykule:
IMPLEMENTATION OF THE PRINCIPLES OF SUSTAINABLE ECONOMY DEVELOPMENT AS A KEY ELEMENT OF THE PRO-ECOLOGICAL TRANSFORMATION OF THE ECONOMY TOWARDS GREEN ECONOMY AND CIRCULAR ECONOMY
Zastosowania technologii Big Data w analizie sentymentu, analityce biznesowej i zarządzaniu ryzykiem opisałem w artykule mego współautorstwa:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
If a Big Data Analytics data center is equipped with advanced generative artificial intelligence technology and is powered by renewable and carbon-free energy sources, can it be described as sustainable, pro-climate, pro-environment, green, etc.?
How to build a sustainable data center based on Big Data Analytics, AI, BI and other Industry 4.0/5.0 technologies and powered by renewable and carbon-free energy sources?
How to build a sustainable data center based on Big Data Analytics, AI, BI and other Industry 4.0/5.0 and RES technologies?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

Does the application of generative artificial intelligence technology and Big Data Analytics enable the improvement of computerized Business Intelligence business management support systems?
The growing volume of data that is processed in companies and enterprises determines the need to involve specialized software and information systems, thanks to which both the analysis of data will be carried out effectively and the results of the analytics carried out will enable the use of the resulting knowledge to support the management processes of the business entity. The issue of the scope of large amounts of data acquired from various sources, their storage and processing is related to Big Data Analytics technology. However, in order to significantly increase the efficiency of processing large sets of data and information with the use of this type of analytics to support the management process of the business entity, computerized, multi-module business intelligence applications are particularly helpful in this regard. The combination of database technologies and analytical platforms of Big Data Analytics and Business Intelligence type applications makes it possible, on the basis of large data sets containing not fully structured and organized data, to generate useful information for a specific entity, as well as concretized and sublimated substantive knowledge used to support the management process of an organization, institution, business entity, etc. In terms of the key objectives of the application of knowledge generated in this way, it is distinguished to improve the quality of business decisions, reduce the risk of making errors during the processes of managing the organization, improve risk management systems, increase the effectiveness of early warning systems of new threats and development opportunities, etc. Analytics conducted on large data sets and implemented using Big Data Analytics and Business Intelligence applications can help in the processes of carrying out restructuring, developing a new strategy, investment project, marketing plan, business remodeling, etc. Analytics based on Business Intelligence applications can be helpful in the processes of supporting the management of various spheres of business activity of companies and enterprises and thus supporting the operation of various departments, including procurement, production, distribution, sales, marketing communication with customers, relations with business contractors, financial or public institutions. Multi-module business intelligence information systems can operate as integrated information systems or can be one of the key elements of such information systems digitally integrating many different aspects of companies, enterprises or other types of entities. Besides, multi-module complex Business Intelligence information systems can be dedicated to handle and support the implementation of specific business processes at different levels of an organization's organizational structure, i.e. they can consist of modules dedicated to handling for operational employees, departmental managers, managers, but also the board of directors and the company's president. Besides, in connection with the development of deep learning technologies carried out using artificial neural networks and generative artificial intelligence technologies, there are opportunities to increase the scale of automation of analytical processes through the use of the aforementioned technologies. The application of artificial intelligence technologies to analytics carried out using Big Data Analytics and artificial intelligence can significantly increase the efficiency of analytical processes and in terms of supporting organizational management processes, can speed up decision-making processes and reduce the risk of errors. A particularly important attribute of such solutions is the ability to perform predictive analysis and forecasting, so that an entrepreneur can spot certain business and economic patterns in good time and forecast future financial performance and development trends more accurately. Thanks to the use of generative artificial intelligence technology, the functionality and usefulness of analytics based on Big Data Analytics and Business Intelligence class systems is significantly increasing.
In view of the rapid development of applications of generative artificial intelligence technology and its implementation into applications and information systems supporting business management processes, I addressed the Research Gate community of Researchers, Scientists, Friends with the above question.
I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Does the application of generative artificial intelligence and Big Data Analytics technologies enable the improvement of computerized Business Intelligence support systems for enterprise management processes?
Does the application of artificial intelligence and Big Data Analytics enable the improvement of computerized Business Intelligence systems?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

How can artificial intelligence help conduct economic and financial analysis, sectoral and macroeconomic analysis, fundamental and technical analysis ...?
How should one carry out the process of training generative artificial intelligence based on historical economic data so as to build a system that automatically carries out economic and financial analysis ...?
How should the process of training generative artificial intelligence be carried out based on historical economic data so as to build a system that automatically carries out sectoral and macroeconomic analyses, economic and financial analyses of business entities, fundamental and technical analyses for securities priced on stock exchanges?
Based on relevant historical economic data, can generative artificial intelligence be trained so as to build a system that automatically conducts sectoral and macroeconomic analyses, economic and financial analyses of business entities, fundamental and technical analyses for securities priced on stock exchanges?
The combination of various analytical techniques, ICT information technologies, Industry 4.0/5.0, including Big Data Analytics, cloud computing, multi-criteria simulation models, digital twins, Business Intelligence and machine learning, deep learning up to generative artificial intelligence, and quantum computers characterized by high computing power, opens up new, broader possibilities for carrying out complex analytical processes based on processing large sets of data and information. Adding generative artificial intelligence to the aforementioned technological mix also opens up new possibilities for carrying out predictive analyses based on complex, multi-factor models made up of various interrelated indicators, which can dynamically adapt to the changing environment of various factors and conditions. The aforementioned complex models can relate to economic processes, including macroeconomic processes, specific markets, the functioning of business entities in specific markets and in the dynamically changing sectoral and macroeconomic environment of the domestic and international global economy. Identified and described trends of specific economic and financial processes developed on the basis of historical data of the previous months, quarters and years are the basis for the development of forecasts of extrapolation of these trends for the following months, quarters and years, taking into account a number of alternative situation scenarios, which can dynamically change over time depending on changing conditions and market and sectoral determinants of the environment of specific analyzed companies and enterprises. In addition to this, the forecasting models developed in this way can apply to various types of sectoral and macroeconomic analyses, economic and financial analyses of business entities, fundamental and technical analyses carried out for securities priced in the market on stock exchanges. Market valuations of securities are juxtaposed with the results of the fundamental analyses carried out in order to diagnose the scale of undervaluation or overvaluation of the market valuation of specific stocks, bonds, derivatives or other types of financial instruments traded on stock exchanges. In view of the above, opportunities are now emerging in which, based on relevant historical economic data, generative artificial intelligence can be trained so as to build a system that automatically conducts sectoral and macroeconomic analyses, economic and financial analyses of business entities, fundamental and technical analyses for securities priced on stock exchanges.
I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Based on relevant historical economic data, is it possible to train generative artificial intelligence so as to build a system that automatically conducts sectoral and macroeconomic analyses, economic and financial analyses of business entities, fundamental and technical analyses for securities priced on stock exchanges?
How should the process of training generative artificial intelligence based on historical economic data be carried out so as to build a system that automatically carries out sectoral and macroeconomic analyses, economic and financial analyses of business entities, fundamental and technical analyses for securities priced on stock exchanges?
How should one go about training generative artificial intelligence based on historical economic data so as to build a system that automatically conducts economic and financial analyses ...?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

How can the application of generative artificial intelligence improve the existing applications of Big Data Analytics and increase the scale of application of these technologies in carrying out analyses of processing large data sets, generating multi-criteria simulation models and carrying out predictive analyses and projections?
The acceleration of the processes of digitization of the economy triggered by the development of the Covid-19 pandemic has resulted in a significant increase in computerization, Internetization, applications of ICT information technologies and Industry 4.0 to various economic processes. There is an increase in applications of specific Industry 4.0 technologies in many industries and sectors of the economy, i.e., such as Big Data Analytics, Data Science, cloud computing, machine learning, personal and industrial Internet of Things, artificial intelligence, Business Intelligence, autonomous robots, horizontal and vertical data system integration, multi-criteria simulation models, digital twins, additive manufacturing, Blockchain, cybersecurity instruments, Virtual and Augmented Reality, and other advanced Data Mining technologies. In my opinion, among others, in the fields of medical therapies, communications, logistics, new online media, life science, ecology, economics, finance, etc., and also in the field of predictive analytics, there is an increase in the applications of ICT information technologies and Industry 4.0/Industry 5.0. Artificial intelligence technologies are growing rapidly as they find applications in various industries and sectors of the economy. It is only up to human beings how and in what capacity artificial intelligence technology will be implemented in various manufacturing processes, analytical processes, etc., where large data sets are processed in the most efficient manner. In addition, various opportunities are opening up for the application of artificial intelligence in conjunction with other technologies of the current fourth industrial revolution referred to as Industry 4.0/5.0. It is expected that in the years to come, applications of artificial intelligence will continue to grow in various areas, fields of manufacturing processes, advanced data processing, in improving manufacturing processes, in supporting the management of various processes, and so on.
I have been studying this issue for years and have presented the results of my research in the article, among others:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How can the application of generative artificial intelligence improve the existing applications of Big Data Analytics and increase the scale of application of these technologies in carrying out analysis of processing large data sets, generating multi-criteria simulation models and carrying out predictive analysis and projections?
How can the application of generative artificial intelligence improve existing applications of Big Data Analytics?
And what is your opinion about it?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

What are the possibilities of applying AI-based tools, including ChatGPT and other AI applications in the field of predictive analytics in the context of forecasting economic processes, trends, phenomena?
The ongoing technological advances in ICT and Industry 4.0/5.0, including Big Data Analytics, Data Science, cloud computing, generative artificial intelligence, Internet of Things, multi-criteria simulation models, digital twins, Blockchain, etc., make it possible to carry out advanced data processing on increasingly large volumes of data and information. The aforementioned technologies contribute to the improvement of analytical processes concerning the operation of business entities, including, among others, in the field of Business Intelligence, economic analysis as well as in the field of predictive analytics in the context of forecasting processes, trends, economic phenomena. In connection with the dynamic development of generative artificial intelligence technology over the past few quarters and the simultaneous successive increase in the computing power of constantly improved microprocessors, the possibilities of improving predictive analytics in the context of forecasting economic processes may also grow.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
What are the possibilities of applying AI-based tools, including ChatGPT and other AI applications for predictive analytics in the context of forecasting economic processes, trends, phenomena?
What are the possibilities of applying AI-based tools in the field of predictive analytics in the context of forecasting economic processes?
And what is your opinion on this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz

Is it possible to build a highly effective forecasting system for future financial and economic crises based on artificial intelligence technology in combination with Data Science analytics, Big Data Analytics, Business Intelligence and/or other Industry 4.0 technologies?
Is it possible to build a highly effective, multi-faceted, intelligent forecasting system for future financial and economic crises based on artificial intelligence technology in combination with Data Science analytics, Big Data Analytics, Business Intelligence and/or other Industry 4.0 technologies as part of a forecasting system for complex, multi-faceted economic processes in such a way as to reduce the scale of the impact of the paradox of a self-fulfilling prediction and to increase the scale of the paradox of not allowing a predicted crisis to occur due to pre-emptive anti-crisis measures applied?
What do you think about the involvement of artificial intelligence in combination with Data Science, Big Data Analytics, Business Intelligence and/or other Industry 4.0 technologies for the development of sophisticated, complex predictive models for estimating current and forward-looking levels of systemic financial, economic risks, debt of the state's public finance system, systemic credit risks of commercially operating financial institutions and economic entities, forecasting trends in economic developments and predicting future financial and economic crises?
Research and development work is already underway to teach artificial intelligence to 'think', i.e. the conscious thought process realised in the human brain. The aforementioned thinking process, awareness of one's own existence, the ability to think abstractly and critically, and to separate knowledge acquired in the learning process from its processing in the abstract thinking process in the conscious thinking process are just some of the abilities attributed exclusively to humans. However, as part of technological progress and improvements in artificial intelligence technology, attempts are being made to create "thinking" computers or androids, and in the future there may be attempts to create an artificial consciousness that is a digital creation, but which functions in a similar way to human consciousness. At the same time, as part of improving artificial intelligence technology, creating its next generation, teaching artificial intelligence to perform work requiring creativity, systems are being developed to process the ever-increasing amount of data and information stored on Big Data Analytics platform servers and taken, for example, from selected websites. In this way, it may be possible in the future to create "thinking" computers, which, based on online access to the Internet and data downloaded according to the needs of the tasks performed and processing downloaded data and information in real time, will be able to develop predictive models and specific forecasts of future processes and phenomena based on developed models composed of algorithms resulting from previously applied machine learning processes. When such technological solutions become possible, the following question arises, i.e. the question of taking into account in the built intelligent, multifaceted forecasting models known for years paradoxes concerning forecasted phenomena, which are to appear only in the future and there is no 100% certainty that they will appear. Well, among the various paradoxes of this kind, two particular ones can be pointed out. One is the paradox of a self-fulfilling prophecy and the other is the paradox of not allowing a predicted crisis to occur due to pre-emptive anti-crisis measures applied. If these two paradoxes were taken into account within the framework of the intelligent, multi-faceted forecasting models being built, their effect could be correlated asymmetrically and inversely proportional. In view of the above, in the future, once artificial intelligence has been appropriately improved by teaching it to "think" and to process huge amounts of data and information in real time in a multi-criteria, creative manner, it may be possible to build a highly effective, multi-faceted, intelligent forecasting system for future financial and economic crises based on artificial intelligence technology, a system for forecasting complex, multi-faceted economic processes in such a way as to reduce the scale of the impact of the paradox of a self-fulfilling prophecy and increase the scale of the paradox of not allowing a predicted crisis to occur due to pre-emptive anti-crisis measures applied. In terms of multi-criteria processing of large data sets conducted with the involvement of artificial intelligence, Data Science, Big Data Analytics, Business Intelligence and/or other Industry 4. 0 technologies, which make it possible to effectively and increasingly automatically operate on large sets of data and information, thus increasing the possibility of developing advanced, complex forecasting models for estimating current and future levels of systemic financial and economic risks, indebtedness of the state's public finance system, systemic credit risks of commercially operating financial institutions and economic entities, forecasting economic trends and predicting future financial and economic crises.
In view of the above, I address the following questions to the esteemed community of scientists and researchers:
Is it possible to build a highly effective, multi-faceted, intelligent forecasting system for future financial and economic crises based on artificial intelligence technology in combination with Data Science, Big Data Analytics, Business Intelligence and/or other Industry 4.0 technologies in a forecasting system for complex, multi-faceted economic processes in such a way as to reduce the scale of the impact of the paradox of the self-fulfilling prophecy and to increase the scale of the paradox of not allowing a forecasted crisis to occur due to pre-emptive anti-crisis measures applied?
What do you think about the involvement of artificial intelligence in combination with Data Science, Big Data Analytics, Business Intelligence and/or other Industry 4.0 technologies to develop advanced, complex predictive models for estimating current and forward-looking levels of systemic financial risks, economic risks, debt of the state's public finance system, systemic credit risks of commercially operating financial institutions and economic entities, forecasting trends in economic developments and predicting future financial and economic crises?
What do you think about this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Warm regards,
Dariusz Prokopowicz

Any background and perspectives?
Who has references on business intelligence and its role in the world rankings of universities, please provide me with that
Significance of big data in business analytics
How can machine learning technology, deep learning and a specific generation of artificial intelligence applied to Big Data Analytics platforms help in the processes of managing the effective operation and growth of an innovative startup?
How should a system architecture built from modules incorporating implemented machine learning, deep learning and specific generation artificial intelligence, Big Data Analytics and other Industry 4.0 technologies be designed to assist in the improvement of computerised Business Intelligence analytics platforms and thus in the processes of managing the effective operation and development of a commercially operating innovative startup?
The development of innovation and entrepreneurship, including the effective development of innovative startups using new technologies in business, is among the key determinants of a country's economic development. Among the important factors supporting the development of innovativeness and entrepreneurship, apart from system facilitations, a favourable tax system, low interest rates on investment loans, available non-refundable financial subsidies, there is also the issue of the possibility of implementing new technologies, including Industry 4. 0, including, but not limited to, technologies such as artificial intelligence, machine learning, deep learning and Big Data Analytics, Internet of Things, digital twins, multi-criteria simulation models, cloud computing, robots, horizontal and vertical data system integration, additive manufacturing, Blockchain, smart technologies, etc., can be helpful in the process of improving the management of economic entities, including service companies, manufacturing enterprises and innovative start-ups. These information technologies and Industry 4.0 can also help to improve Business Intelligence used in business management. The key issue is the proper combination of applied Industry 4.0 technologies to create computerised platforms supporting the processes of managing both the current, operational functioning of economic entities and in the processes of forecasting the determinants of the development of companies and enterprises, in the creation of forecasting models of simulation of development for a specific economic entity, which may also be an innovative start-up. In recent years, attempts have been made in larger business entities, corporations, financial institutions, including commercial banks, to create computerised Business Intelligence analytical platforms improved through a combination of applied technologies such as machine learning, deep learning and a specific generation of artificial intelligence applied to Big Data Analytics platforms. Such processes for improving Business Intelligence analytical platforms are carried out in order to support the management of the effective operation and development of a commercially operating specific business entity. Therefore, in a situation where specific financial resources are available to create analogous Business Intelligence analytical platforms, it is possible to apply an analogous solution to support the management of the effective operation and development of a commercially functioning specific innovative start-up.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How can machine learning technology, deep learning and a specific generation of artificial intelligence applied to Big Data Analytics platforms help in the processes of managing the effective operation and development of an innovative startup?
How should a system architecture built from modules containing implemented machine learning technology, deep learning and a specific generation of artificial intelligence, Big Data Analytics and other Industry 4.0 technologies be designed to assist in the improvement of computerised Business Intelligence analytics platforms and thus in the processes of managing the effective operation and development of a commercially operating innovative startup?
And what is your opinion on this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best wishes,
Dariusz Prokopowicz

What are the possibilities for applications of artificial intelligence and Big Data Analytics in carrying out multi-criteria economic and financial analyses of business entities, analyses carried out on computerised Business Intelligence platforms?
What are the potential applications of machine learning, deep learning, artificial intelligence, Big Data Analytics and other Industry 4.0 technologies in conducting multi-criteria economic and financial analyses of the historical and current performance of economic entities and making predictions about the future development of their business, analyses carried out on computerised Business Intelligence platforms?
As a result of technological advances, the potential for the application of machine learning, deep learning, artificial intelligence, Big Data Analytics and other Industry 4.0 technologies to perform multi-criteria economic and financial analyses of the historical and current functioning of businesses and to make predictions about the future development of their business, analyses carried out on computerised Business Intelligence platforms, is rapidly increasing. New ICT information technologies and Industry 4.0, including Artificial Intelligence, Machine Learning, Deep Learning, Big Data Analytics but also Data Science, Smart Technologies, Cloud Computing, Machine Learning, Personal and Industrial Internet of Things, Autonomous Robots, Horizontal and Vertical Data System Integration, Multi-Criteria Simulation Models, Digital Twins, Additive Manufacturing, Blockchain, Cyber Security Instruments, Virtual and Augmented Reality and other Advanced Data Mining technologies support the management processes of a company, enterprise or financial institution. In recent years, the aforementioned new technologies are helping to improve the management processes of supply logistics, procurement, production, service offering; marketing communication and customer relationship management; risk management; cyber security management; economic and financial analysis management, financial auditing, etc. Therefore, within the framework of the technological advances taking place, including the increasing computational capabilities of successive generations of processors and operational memory installed in computers, increasing disk capacities, storage media, increasing data transfers, etc., the possibilities of applying artificial intelligence and Big Data Analytics in carrying out multi-criteria economic and financial analyses of business entities, analyses carried out on computerised Business Intelligence platforms, are successively increasing. Consequently, the possibilities for the application of multi-criteria analytics carried out on computerised Business Intelligence platforms are also increasing year on year, which also contributes to the improvement of organisational management processes.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
What are the possibilities for the application of Machine Learning, Deep Learning, Artificial Intelligence and Big Data Analytics and other Industry 4.0 technologies in carrying out multi-criteria economic and financial analyses of the historical and current performance of business entities and making predictions about the future development of their business, analyses carried out on computerised Business Intelligence platforms?
What do you think about this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best wishes,
Dariusz Prokopowicz

How can artificial intelligence such as ChatGPT and Big Data Analytics be used to analyse the level of innovation of new economic projects that new startups that are planning to develop implementing innovative business solutions, technological innovations, environmental innovations, energy innovations and other types of innovations?
The economic development of a country is determined by a number of factors, which include the level of innovativeness of economic processes, the creation of new technological solutions in research and development centres, research institutes, laboratories of universities and business entities and their implementation into the economic processes of companies and enterprises. In the modern economy, the level of innovativeness of the economy is also shaped by the effectiveness of innovation policy, which influences the formation of innovative startups and their effective development. The economic activity of innovative startups generates a high investment risk and for the institution financing the development of startups this generates a high credit risk. As a result, many banks do not finance business ventures led by innovative startups. As part of the development of systemic financing programmes for the development of start-ups from national public funds or international innovation support funds, financial grants are organised, which can be provided as non-refundable financial assistance if a startup successfully develops certain business ventures according to the original plan entered in the application for external funding. Non-refundable grant programmes can thus activate the development of innovative business ventures carried out in specific areas, sectors and industries of the economy, including, for example, innovative green business ventures that pursue sustainable development goals and are part of green economy transformation trends. Institutions distributing non-returnable financial grants should constantly improve their systems of analysing the level of innovativeness of business ventures planned to be implemented by startups described in applications for funding as innovative. As part of improving systems for verifying the level of innovativeness of business ventures and the fulfilment of specific set goals, e.g. sustainable development goals, green economy transformation goals, etc., new Industry 4.0 technologies implemented in Business Intelligence analytical platforms can be used. Within the framework of Industry 4.0 technologies, which can be used to improve systems for verifying the level of innovativeness of business ventures, machine learning, deep learning, artificial intelligence (including e.g. ChatGPT), Business Intelligence analytical platforms with implemented Big Data Analytics, cloud computing, multi-criteria simulation models, etc., can be used. In view of the above, in the situation of having at one's disposal appropriate IT equipment, including computers equipped with new generation processors characterised by high computing power, it is possible to use artificial intelligence, e.g. ChatGPT and Big Data Analytics and other Industry 4.0 technologies to analyse the level of innovativeness of new economic projects that plan to develop new start-ups implementing innovative business solutions, technological, ecological, energy and other types of innovations.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How can artificial intelligence such as ChatGPT and Big Data Analytics be used to analyse the level of innovation of new economic projects that plan to develop new startups implementing innovative business solutions, technological innovations, ecological innovations, energy innovations and other types of innovations?
What do you think?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Warm regards,
Dariusz Prokopowicz

I want to do a thesis on business intelligence application and development but I can't seem to find the right topic to go with. Please, if you have any ideas you can share or don't mind me working with for my thesis, I will be very grateful. Thank you
One of my master students is currently conducting a preliminary study to find out the maturity of the Cross Industry Standard Process for Big Data (CRISP4BigData) for use in Big Data projects. I would like to invite all scientists, Big Data experts, project managers, data engineers, data scientists from my network to participate in the following survey. Feel free to share!
I’m working on a research on how business intelligence tool like oracle apex can tackle health inequality. I will really appreciate if anyone can explain why it is used for tackling health inequality.
Thank you.
Commercial banks are increasingly worried about competition from fintechs, including online technology companies that expand the range of financial and pre-financial services. Commercial banks are more and more actively using IT technologies of online banking, building Business Intelligence data processing platforms, extending Big Data database systems, developing integrated risk management systems and conducting advertising campaigns on social media websites. In view of the above, large commercial banks have the opportunity to conduct a sentiment analysis on data collected in Big Data database systems for the purpose of analyzing the expectations and opinions of Internet users regarding, for example, financial services. Information obtained from the Internet and processed in the aforementioned manner can be used for more precise risk analysis, credit risk management, planning subsequent advertising campaigns, modifying the financial services offer in line with changing expectations of Internet users, searching for clients on social media portals. In this way, interdisciplinary analytical processes are also developed at commercial banks, for which the information from the websites of social media portals is the source of data.
Do commercial banks have a chance to win in this matter in competition with the fintech technology companies operating on the Internet?
Besides, What is the effectiveness of online advertising campaigns run by commercial banks?
Please, answer, comments.
I invite you to the discussion.

first I need to analyze and try to answer for predictive and prescriptive maintenance questions
dear community, I need some sources for some data science project or machine learning project related to analyzing the google analytics and Facebook business data , your help is appreciated.
Identifying the level of intelligence maturity in the agricultural sector and comparing BI maturity models to design a specific model of agricultural intelligence
What will be the future applications of analytics of large data sets conducted in the computing cloud on computerized Business Intelligence analytical platforms in Big Data database systems in enterprise logistics management?
The analytics conducted on computerized Business Intelligence platforms is one of the key advanced information technology technologies of the fourth technological revolution, known as Industry 4.0. The current technological revolution described as Industry 4.0 is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.
The analytics conducted on computerized Business Intelligence platforms currently supports business management processes, including logistics management.
In my opinion, the use of analytics of large data sets conducted in the computing cloud on computerized Business Intelligence analytical platforms in Big Data database systems in enterprise logistics management, including supply logistics, production logistics, provision of services and distribution of manufactured products and services, is currently growing.
The analytics conducted on large data sets conducted in the cloud computing on Business Intelligence computerized platforms in Big Data database systems makes it particularly easy to identify opportunities and threats to business development, allows for quick generation of analytical reports on selected issues in the economic and financial situation of the business entity. In this way, the generated reports can be helpful in the processes of enterprise logistics management, including supply logistics, production logistics, provision of services and distribution of manufactured products and services.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
What will be the future applications of analytics of large data sets conducted in the computing cloud on computerized Business Intelligence analytical platforms in Big Data database systems in enterprise logistics management?
Please reply
I invite you to the discussion
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
I invite you to discussion and cooperation.
Best wishes

The current technological revolution, known as Industry 4.0, is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.
In connection with the above, I would like to ask you:
Which information technologies of the current technological revolution Industry 4.0 to the greatest extent support the enterprise management process?
Please reply
Best wishes

Such a system can be a Business Intelligence analytical platform connected to the Big Data database system, where information from the Internet is collected, collected, processed and analyzed, including comments from Internet users entered into social media portals.
On the basis of this data, analytics reports are created in the Business Intelligence system describing changes in interest, consumer preferences for specific products and services, as well as changes in the company's brand assessment that offers a specific product or service offer to the market.
These reports can be very tangible in the business management process, including they can support decision-making in the field of production planning as well as the distribution process, sales organization in the form via the Internet, in the form of e-commerce.
Do you agree with me on the above matter?
In the context of the above issues, the following question is valid:
How to build a decision support system in the field of selling on the Internet, online store, e-commerce?
Please reply
I invite you to the discussion
Thank you very much
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
I invite you to discussion and cooperation.
Best wishes

The goal of predictive analysis is to develop predictions for the development of complex, multifaceted processes in various fields of science, industry, economy or other spheres of human activity. In addition, predictive analysis may refer to objectively performing processes such as natural phenomena, climate change, geological, cosmic etc.
Predictive analysis should be based on taking into account in the analytical methodology possible the most modern prognostic models and a large amount of data necessary to perform the most accurate predictive analysis. In this way, the result of the prediction analysis performed will be the least subject to the risk of analytical error, ie an incorrectly designed forecast.
Predictive analysis can be improved by using computerized modern information technologies, which include computing in the cloud of large data sets stored in Big Data database systems. In the predictive analysis, Business Intelligence analytics and other innovative information technologies typical of the current fourth technological revolution, known as Industry 4.0, can also be used.
The current technological revolution known as Industry 4.0 is motivated by the development of the following factors:
Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies. On the basis of the development of the new technological solutions in recent years, dynamically developing processes of innovatively organized analyzes of large information sets stored in Big Data database systems and computing cloud computing for the needs of applications in such areas as: machine learning, Internet of Things, artificial intelligence, Business Intelligence are dynamically developing.
For the abovementioned application examples, one can add predictive analyzes of subsequent, other fields of application of advanced technologies for the analysis of large data sets such as Medical Intelligence, Life Science, Green Energy, etc. Processing and multi-criteria analysis of large data sets in Big Data database systems is carried out according to V4 concepts, ie Volume (meaning a large number of data), Value (large values of certain parameters of the analyzed information), Velocity (high speed of new information) and Variety (high variety of information).
The advanced information processing and analysis technologies mentioned above are used more and more often for the needs of conducting predictive analyzes concerning, for example, marketing activities of various business entities that advertise their offer on the Internet or analyze the needs in this area reported by other entities, including companies, corporations, institutions financial and public. More and more commercial business entities and financial institutions conduct marketing activities on the Internet, including on social media portals.
More and more public institutions and business entities, including companies, banks and other entities, need to conduct multi-criteria analyzes on large data sets downloaded from the Internet describing the markets on which they operate, as well as contractors and clients with whom they cooperate.
On the other hand, there are already specialized technology companies that offer this type of analytical services, including offering predictive analysis services, develop custom reports, which are the result of multicriteria analyzes of large data sets obtained from various websites and from entries and comments. contained on social media portals based on sentiment analyzes of the content of entries in the comments of Internet users.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
How can you improve the process of predictive analysis?
Please reply
I invite you to discussion and scientific cooperation
Dear Colleagues and Friends from RG
The key aspects and determinants of the applications of modern computerized information technologies for data processing in Big Data and Business Intelligence database systems for the purpose of conducting predictive analyzes are described in the following publications:
I invite you to discussion and cooperation.
Best wishes

How to obtain currently necessary information from Big Data database systems for the needs of specific scientific research and necessary to carry out economic, business and other analyzes?
Of course, the right data is important for scientific research. However, in the present era of digitalization of various categories of information and creating various libraries, databases, constantly expanding large data sets stored in database systems, data warehouses and Big Data database systems, it is important to develop techniques and tools for filtering large data sets in those databases data to filter out of terabytes of data only information that is currently needed for the purpose of conducted scientific research in a given field of knowledge, for the purposes of obtaining answers to a given research question and for business needs, eg after connecting these databases to Business Intelligence analytical platforms. I described these issues in my scientific publications presented below.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
How to obtain currently necessary information from Big Data database systems for the needs of specific scientific research and necessary to carry out economic, business and other analyzes?
Please reply
I invite you to the discussion
Thank you very much
Dear Colleagues and Friends from RG
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
I invite you to discussion and cooperation.
Best wishes

What kind of scientific research dominate in the field of Business Intelligence?
What are the important topics in the field: Business Intelligence?
Business entity management processes are more and more often supported by computerized Business Intelligence platforms that facilitate multi-criteria analysis and reporting.
Probably in the future, the business analyst will be supported by artificial intelligence.
It would be a great advance in the field of automation and objectification of multi-criteria economic analyzes of business entities.
Complex, multi-criteria analyzes regarding the verification of large companies' operations require aggregation and analytical processing of large data sets in Big Data database systems.
However, in what direction will technological progress be realized in this field?
In the future, as part of the progressing computerization of analytical processes, it will be possible to implement artificial intelligence to the processes of analyzing large collections of information collected in Big Data database systems.
Apparently, we are now living in the era of the fourth technological revolution, known as Industry 4.0.
The previous three technological revolutions:
1. The industrial revolution of the eighteenth and nineteenth centuries, determined mainly by the industrial application of the invention of a steam engine.
2. Electricity era of the late nineteenth century and early twentieth century.
3. The IT revolution of the second half of the twentieth century determined by computerization, the widespread use of the Internet and the beginning of the development of robotization.
The current fourth technological revelation, known as Industry 4.0, is motivated by the development of the following factors:
- artificial intelligence,
- cloud computing,
- machine learning,
- Big Data database technologies,
- Internet of Things.
On the basis of the development of these IT instruments and technologies, business analytics of companies such as Business Intelligence and the above-mentioned areas have been dynamically developing in recent years.
In view of the above, I turn to you with the following question: In what direction will the current technological revolution, known as Industry 4.0, develop?
Please, answer, comments. I invite you to the discussion.
Dear Colleagues and Friends from RG
Some of the currently developing aspects and determinants of the applications of data processing technologies in Big Data database systems are described in the following publications:
I invite you to discussion and cooperation.
Best wishes

Does the development and implementation of new information technologies for banking affect the processes of improving the security of online banking systems?
Improvement of online banking security systems can currently be significantly determined, among others, by the implementation of new information technologies for banking.
Are the processes of improving internet banking security systems currently determined by the implementation of new information technologies, i.e. by implementing banking data processing technologies in Big Data database systems, Business Intelligence based analytics, implementation of Blockchain technology and artificial intelligence.
Do you think that the processes of improving internet banking security systems are currently determined by the implementation of new information technologies for banking?
Please reply
Best wishes

Does the combination of Big Data database technologies and Business Intelligence analytics enable the improvement of conducting various economic, financial and other analyzes?
In my opinion, the scope of synergy and possibilities of combining applications of various advanced information processing technologies, including data analysis eg on Business Intelligence platforms based on large data sets collected in Big Data database systems for the purpose of improving information security management processes, including information transferred, increases. on the Internet, collected in Big Data database systems and used to carry out various economic, financial and other analyzes.
Please reply
I invite you to the discussion
Thank you very much
Best wishes

Dear all,
I am finding some documents, papers, or book focused on technologies for Business Intelligence (BI). For example, Technologies Supporting Organisation Memory, Technology Enabling Information Integration, Technologies Enabling Decision Making, Technology Enabling Presentation.
Please recommend any document you know.
Thank you
Hi,
I want to do a thesis on Data Analysis, Business Intelligence or Data Visualisation but I can't seem to find the right topic to go with. I actually have to submit a proposal in few weeks time but so far I've not found any and I don't know what to do. Please, if you have any idea you can share or don't mind me working with for my thesis, I will be very grateful. Thank you
I propose an analysis of changes in behavioral behavior of consumers, business entities and other participants of individual markets, which can be observed on the basis of the analysis of entries, comments, posts, etc. typed by users of social media portals.
These studies are carried out as part of the sentiment analysis on data downloaded from the Internet and collected in Big Data database systems.
What is more interesting is the Business Intelligence type of analysis carried out in business entities using specialized software. The development of analytical platforms operating in the Business Intelligence formula automates and objectivises economic, financial and technical-economic analyzes regarding the functioning of business entities.
Please, answer, comments. I invite you to the discussion.

The development of accounting and financial reporting should be correlated with technological progress in this area, i.e. should take into account the development of IT applications that are commonly used in accounting, accounting and financial reporting in business entities. In addition, in recent years, instrumentalization, standardization and computerization of conducting economic, financial, indicator, fundamental analyzes, etc. supporting reporting processes have been developing rapidly.
In addition, computerized analytics concerning the processing of data generated, among others, in accounting systems on Business Intelligence platforms are also developing. Analyzes carried out in the cloud using Business Intelligence based on data collected in Big Data database systems support financial management processes and management of the entire economic activity conducted by a specific company or financial, public, etc. institute.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
What are the main determinants of the development of accounting and financial reporting?
Please reply
The issues of the use of information contained in Big Data database systems for the purposes of carrying out Business Intelligence analyzes are described in the publications:
I invite you to discussion and scientific cooperation
Best wishes

What kind of scientific research dominate in the field of Business Intelligence analytics?
Please, provide your suggestions for a question, problem or research thesis in the issues: Business Intelligence analytics.
Please reply. I invite you to the discussion
Dear Colleagues and Friends from RG
The key aspects and determinants of applications of data processing technologies in Big Data database systems are described in the following publications:
I invite you to discussion and cooperation.
Best wishes

as to my supply chain thesis I am interested in supply chain performance, KPI tree and business intelligence
In my opinion, the combination of technologies typical of the technological revolution known as Industry 4.0 may turn out to be one of the key determinants of civilization progress in the 21st century.
At present, in the age of the technological revolution known as the 4.0 industry, new concepts of technological management or Internet-based companies are being created.
The technological revolution in recent years, known as Industry 4.0, is motivated by the development of the following factors:
Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence.
In addition, in the knowledge-based economy, the important areas of knowledge and technologies that are developed are primarily the development of data processing analytics in Business Intelligence enterprises, the development of life science technologies, biotechnology, eco-innovation, RES energy, medical intelligence, etc.
On the basis of the development of the new technological solutions mentioned in recent years, the processes of innovatively organized analyzes of large information collections gathered in Big Data database systems dynamically develop.
In view of the above, I would like to ask you: Which technologies will determine the development of civilization in the 21st century?
Please, answer, comments. I invite you to the discussion.

Hello dear community,
I am looking for a valid and empirically tested conceptual model that links the following concepts: Business intelligence systems, decision making process and decision quality
Thanks for your help
Which of the algorithms identified in artificial intelligence can be used to design an intelligent management dashboard with the help of Devops that increase the performance of an organization by implementing enterprice architecture in it? The purpose of smart management dashboard with the help of these algorithms and devops in enterprise architecture
If in many research works, for the purposes of conducted scientific research, the analysis of information collected in Big Data database systems is already used, more and more attempts will be made by various research centers to use data processing in the cloud data collected in Big Data database systems. The data mining technology, artificial intelligence, business intelligence and other advanced information and analytical technologies will also be added to this.
I invite you to the discussion

Business entity management processes are more and more often supported by computerized Business Intelligence platforms that facilitate multi-criteria analysis and reporting.
Complex, multi-criteria analyzes regarding the verification of large companies' operations require aggregation and analytical processing of large data sets in Big Data database systems.
Specialized IT companies produce applications that help in conducting economic analyzes, i.e. the Business Intelligence platform.
More and more often, large and medium-sized companies use these platforms to adapt them to the specifics of their business.
However, in what direction will technological progress be realized in this field?
In view of the above, the current question is: Will the artificial intelligence for Business Intelligence application be implemented as part of the progressing computerization of analytical processes?
Please, answer, comments. I invite you to the discussion.
How should there be an active cooperation between business and science? How should the development of clusters and agreements between cooperating enterprises and science centers, scientific institutes and universities be facilitated in the economic policy of the state?
In my opinion, there should be an active cooperation between business and science. I believe that in the economic policy of the state it is necessary to develop the facilitation of the development of clusters and agreements of cooperating enterprises with science centers, with research institutes and universities. Business development should result from scientific knowledge. Businessmen should consult scientists about business development. Scientists are more and more often engaged as consultants working on the needs of business. Entrepreneurs should use the analytical tools developed by scientists, for example in the area of improvement of business analytics tools, developed computerized tools for advanced information processing, eg in Big Data database systems using Business Intelligence analytical platforms. But this is just an example of this type of cooperation between business and science.
On the other hand, it happens more and more often that researchers and scientists start startups or develop research programs, the effect of which is to create a new type of material or technology, innovative solutions. Then, such innovative solutions, which were created in research laboratories, are increasingly implemented in industry. It happens that the state co-finances large research programs, such as space exploration programs. During these high-budget research programs, new technologies are created that are used in the production of many products offered to consumers or become the basis for the creation of new technological solutions implemented in the mass production of various types of products or services.
In addition, new business and economic concepts are developed and developed, such as the concepts of sustainable pro-ecological economic development, the important element of which is the creation and implementation of eco-innovations into the industry, eg the purpose of developing new renewable energy sources. Such processes, whose aim is to reform the energy sector as quickly as possible and convert classic energy sources based on the combustion of minerals to environmentally friendly renewable energy sources are an example of necessary reforms that can be effectively implemented through cooperation of businessmen with scientists and design and implementation of large infrastructure investments and construction of a power plant for the production of electricity as part of the development of renewable energy sources from financial resources of private companies in the financial support of the state.
In connection with the above, there are more and more examples of synergies of development of private or state-supported investment ventures and developing business with the world of science. The state, as part of pro-development state interventionism, should develop its innovation and development policy as a key element of pro-development economic policy, within which it should support, as well as financially and actively, enterprises and the world of science. As part of this activation, facilitations should be created, for example through a system of tax breaks for the development of clusters and agreements between cooperating enterprises and science centers, scientific institutes and universities. This is a particularly important pro-development element in knowledge-based economies.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
Should business cooperation with science develop? How to support the development of business cooperation with science? How should there be an active cooperation between business and science? How should the development of clusters and agreements between cooperating enterprises and science centers, scientific institutes and universities be facilitated in the economic policy of the state?
Please reply
I invite you to the discussion
Thank you very much
Best wishes

The current technological revolution, known as Industry 4.0, is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.
In connection with the above, I would like to ask you:
Is the process of conducting economic analyzes improved thanks to the development of information technology Industry 4.0?
For example, whether through the use of information technologies in analytical processes such as database technologies for collecting and processing, analyzing large data sets in Big Data database systems, in cloud computing, using the Internet of Things, artificial intelligence, economic analyzes carried out on computerized platforms Business Intelligence - it is possible to effectively analyze much larger amounts of economic data concerning individual companies, their contractors and the economic, market and macroeconomic environment than before, ie a few years ago when these technologies were not used while carrying out economic, fundamental and financial, indicative analyzes e.t.c.?
Please reply
Best wishes

Mentioning above keywords phrase in google search provides multiple outcomes, mostly articles from online magazines like CIO, Granter and more plus few pdf docs from different sources. Looking forward to have more comprehensive case studies on stated subject matter focused on a particular company preferably / industry / region. Thanks in advance for help !
I am looking for the following :
"Failure of business intelligence case studies"
"Failure of Artificial Intelligence case studies"
"Failure of social-media case studies"
The analytics conducted on computerized Business Intelligence platforms is one of the key advanced information technology technologies of the fourth technological revolution, known as Industry 4.0.
The current technological revolution, known as Industry 4.0, is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.
The analytics conducted on computerized Business Intelligence platforms currently supports business management processes, facilitates identification of opportunities and threats to business development, allows for quick generation of analytical reports on selected issues in the economic and financial situation of the business entity.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
What future applications of analytics will be developed on computerized Business Intelligence platforms?
Please reply
I invite you to the discussion
The issues of the use of information contained in Big Data database systems for the purposes of conducting Business Intelligence analyzes are described in the publications:
I invite you to discussion and cooperation.
Best wishes

Do the results of conducted analyzes using Big Data database technologies and Business Intelligence analytics enable improving the accuracy of conducted economic and financial analyzes and other analyzes of the fundamental analysis type and other analyzes of economic effectiveness, economic and financial situation, property valuation, determining the development perspectives of enterprises and improvement of credit risk management processes?
In the context of the above discussion, another question arises:
- Is it possible to improve the credit risk management processes as a result of the use of Big Data database technologies and Business Intelligence analytics for fundamental analysis and other analyzes regarding the economic performance research, economic and financial situation, property valuation, determining business development perspectives?
- Do the results of conducted analyzes using Big Data database technologies and Business Intelligence analytics allow to improve the accuracy of conducted analyzes and increase the probability of prediction, forecasted phenomena and economic processes occurring?
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
Does the use of Big Data database technologies and Business Intelligence analytics for analytical processes of the analysis of the economic and financial situation of enterprises enable the improvement of credit risk management processes in commercial banks?
Please reply
I invite you to the discussion
Thank you very much
Dear Colleagues and Friends from RG
The issues of the use of information contained in Big Data database systems for the purposes of carrying out Business Intelligence analyzes are described in the publications:
I invite you to discussion and cooperation.
Thank you very much
Best wishes

Is the role of strategic management changing in the context of current economic processes and the development of new information technologies typical of the current fourth technological revolution, known as Industry 4.0?
Strategic management is an important area of management in the context of management of both individual enterprises (microeconomically) as well as domestic economic policy (macroeconomics).
In connection with the development of internationally operating corporations, strategic management acquires a new character, it becomes a part of the study of information and economic globalization processes.
In addition, strategic management can also change its charler in relation to processes such as prolonged business cycles, shortened life cycles of products, increased importance of information, technology, innovation, etc. as particularly important production factors in knowledge-based enterprises and economies in which an ever-increasing role of fully computerized advanced information processing technology, ie technologies typical of the current fourth technological revolution, known as Industry 4.0.
The current technological revolution, known as Industry 4.0, is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.
Do you agree with my opinion on this matter?
In view of the above, I am asking you the following question:
Is the role of strategic management changing in the context of current economic processes?
Please reply
I invite you to the discussion
Thank you very much
Best wishes

Greetings,
I am a Ph.D. student and have the following assignmnet:
Research in databases and business intelligence. Your task for this week is to recreate an experiment conducted in a recent research paper. Select a study to recreate which has been published in the last two years.
Where can I find experiments that I can do at home?
Thank you,
Jack