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

Article OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL I...

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

Article APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTEL...

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