Various hedge funds do it all the time. Please refer to their state of the art and plentiful documentation.

Various hedge funds do it all the time. Please refer to their state of the art and plentiful documentation.

these tools will be very helpful to fintech and crowdfunding platform, you may read the related papers of this nascent technologies..

In general BigData belongs to analyse large-scale data sets and BI can help taking informed business decisions, but usually structured data is considered for strategic evaluation. I think you can explore analyzing unstructured data types ( weblogs, social media, email, sensors, and photographs etc) too that can unleash more powerful insights to ensure economic growth of business.

Dear Colleagues and Friends from RG,

I propose to add to this discussion considerations on the following important issue:

The use of sentiment analysis and research processes carried out on Big Data Analytics analytical platforms for the needs of SWOT analysis to determine development perspectives, including the definition of innovative startup development strategies.

For the purposes of analyzing issues related to Big Data Analytics research processes in the applications of SWOT analysis and defining the strategy for the development of innovative startups, I formulated the following thesis that in my opinion the possibilities of using sentiment analysis and research processes carried out on Big Data Analytics analytical platforms to improve the processes of conducting SWOT analysis, including the definition of development perspectives, including the definition of development strategies for innovative startups and other business entities.

In order to verify the above research thesis, I suggest continuing discussions in the field of Big Data Analytics research processes in the applications of SWOT analysis and defining the strategy for the development of innovative startups, as well as in answering the following question:

Can sentiment analysis carried out on data obtained from the Internet and analytics based on Big Data Analytics help to carry out SWOT analysis in order to determine development perspectives, including the definition of innovative startup development strategies?

Below are particularly important determinants of issues related to Big Data Analytics research processes in the applications of SWOT analysis and defining the strategy for the development of innovative startups. The conclusions of this discussion in key aspects of the discussed issues confirm the formulated research thesis. To the above discussion, I would like to add the following conclusion, summarized as a summary of my previous considerations on the topic: The use of sentiment analysis and research processes carried out on Big Data Analytics analytical platforms for the purposes of conducting SWOT analysis to determine development perspectives, including defining the strategy for the development of innovative startups.

SWOT analysis is often used as part of various analytical studies describing the economic and financial situation and development perspectives of enterprises, public institutions and other entities due to its universal nature and simplicity. Despite its simplicity, it has many positive features and has become a component of many other, much more complex analytical processes. SWOT analysis is one of the simplest analytical methods used to diagnose the strengths and weaknesses of the functioning of a particular entity as well as the opportunities and threats to the development of the analyzed enterprise. SWOT analysis is the simplest method for determining a development strategy for an economic entity. It can also be helpful in defining the strategic mission of a given enterprise. Therefore, the SWOT analysis is part of such studies as creditworthiness analysis, business plan, prospectus, analytical report prepared for the purposes of analyzing the possibilities and risk of an investment project, strategic and marketing plan, due diligence, fundamental analysis of investment in securities, process analysis enterprise risk management, innovative start-up development plan, etc.

ICT and Industry 4.0 information technologies are used in the development of advanced data processing technologies and Big Data analytics and Data Science analytics, Data Analytics used in economics, finance and management of organizations, including enterprises, financial and public institutions. In my opinion, scientific research confirms the strong correlation between the development of Big Data technology, Data Science analytics, Data Analytics and the effectiveness of the use of knowledge resources. I believe that the development of Big Data technology and Data Science analytics, Data Analytics and other ICT information technologies, multi-criteria technology, advanced processing of large information sets, and Industry 4.0 technology increases the efficiency of using knowledge resources, including in the field of economics, finance and organization management. In recent years, ICT information technologies, Industry 4.0 etc. have been developing dynamically and are used in knowledge-based economies in particular. These technologies are used in scientific research and business applications in commercial enterprises and in financial and public institutions.

Due to the growing importance of this issue in knowledge-based economies, an important issue is the analysis of the correlation between the development of Big Data technology and Data Science, Data Analytics, Business Intelligence and the effectiveness of using knowledge resources to solve key problems of civilization development, e.g. in the implementation programs for the quick implementation of the principles of sustainable pro-ecological development in economic processes in accordance with the green economy philosophy and the financing of programs for the creation and implementation of ecological innovations, and the urgent implementation of necessary ecological reforms. The goal of these pro-ecological business venture programs is to reduce the level of environmental pollution and slow down the global warming process. However, this is only one of the key global problems, the solution of which may be conditioned by the question of the possibility of increasing the efficiency of using large resources of knowledge accumulated in Big Data databases in knowledge-based economies. In connection with the above, I suggest the following research questions that may inspire you to implement important and interesting research projects:

Are there studies that verify the correlation between the development of Big Data technology and Data Science analytics, Data Analytics, Business Intelligence and other ICT information technologies and advanced data processing Industry 4.0 and the effectiveness of the use of knowledge resources, including in the field of economics, finance and management of organizations, including enterprises, financial and public institutions? In recent years, there have been more and more media reports that in many countries there has been a significant increase in environmental pollution and a global acceleration of the global warming process. The problem is serious because the pace of the global warming process has significantly accelerated in recent years. However, this is only one of many key problems in the development of human civilization to be urgently solved in the 21st century. It is therefore necessary to increase the efficiency of processing knowledge resources in order to find faster solutions to key problems of civilization development. The use of Big Data, Data Science, Data Analytics, Business Intelligence and other ICT information technologies as well as advanced data processing Industry 4.0 in the processing of knowledge resources should contribute to increasing the efficiency of knowledge resource processing in knowledge-based economies, including in the field of economics and finance.

The information and communication technologies listed above, combined with the improvement of ICT technologies and the implementation of Business Intelligence analytics into the processes of economic and financial, economic, macroeconomic and market analyzes may be instrumental instruments helpful in the efficient and effective management of economic, investment processes and enterprises, including analyzes carried out for the purposes of improving marketing activities in enterprises. More and more companies, banks and other entities need to carry out multi-criteria analyzes on large datasets downloaded from the Internet describing the markets in which they operate and contractors and clients with whom they cooperate. On the other hand, there are already specialized technology companies that offer this type of analytical services, prepare commissioned reports, which are the result of such multi-criteria analyzes of large data sets obtained from various websites and from entries and comments contained on social media portals.

An important research technique that has been developing in recent years, the effects of which are used for the purposes of marketing activities of companies, is sentiment analysis carried out on large data sets collected in the Big Data database systems downloaded from the Internet. In order to group the behavior of social media users into specific classes of behavior, these classes must first be defined. Sentiment analysis using large data sets collected from entries and comments from social media portals and transferred to Big Data database platforms can be helpful. Then, when observing the changes in certain types of behavior of users of social media portals, you can analyze the data collected in Big Data according to these observations. In addition, a useful tool can be an analysis of the behavior of users of social media portals on the basis of current posts, entries and comments on specific social media pages, statistical analysis of comments on specific topics of posts. This type of research is carried out by online technology companies that run social media portals and use the results of these studies to develop their viral marketing services, because this field of marketing is a key determinant of revenue generated by these companies from advertising sales on social media portals.

In recent years, the scope of applications of Big Data technology and Data Science analytics, Data Analytics in economics, finance and management of organizations, including enterprises, financial and public institutions, has been increasing. Therefore, the importance of implementing analytical instruments for advanced processing of large data sets in enterprises, financial and public institutions, i.e. the construction of Big Data Analytics platforms to support organization management processes in various aspects of operations, including the improvement of customer relations, is also growing. In my opinion, scientific research confirms the strong correlation between the development of Big Data technology, Data Science analytics, Data Analytics and the effectiveness of the use of knowledge resources. I believe that the development of Big Data technology and Data Science analytics, Data Analytics and other ICT information technologies, multi-criteria technology, advanced processing of large information sets, and Industry 4.0 technology increases the efficiency of using knowledge resources, including in the field of economics, finance and organization management. In recent years, ICT information technologies, Industry 4.0 etc. have been developing dynamically and are used in knowledge-based economies in particular. These technologies are used in scientific research and business applications in commercial enterprises and in financial and public institutions. Due to the growing importance of this issue in knowledge-based economies, an important issue is the analysis of the correlation between the development of Big Data technology and Data Science, Data Analytics, Business Intelligence and the effectiveness of using knowledge resources to solve key development problems of business entities, including innovative ones startups. In view of the above, the scope of applications of Big Data technology and Data Science and Data Analytics analytics as well as the sentiment analysis of data downloaded from the Internet in applications of conducting SWOT analysis, including development perspectives, including the definition of development strategies for innovative startups and other business entities, has been increasing in recent years.

I conduct research in this area. The conclusions of the research I published in scientific publications that are available on the Research Gate portal. I invite you to cooperation.

In accordance with the above, in my opinion, the possibilities of using sentiment analysis and research processes carried out on Big Data Analytics analytical platforms are increasing in order to improve SWOT analysis processes, including the definition of development perspectives, including the definition of development strategies for innovative startups and other business entities.

Do you agree with me on the above matter?

I conduct research in this area. The conclusions of the research I published in scientific publications that are available on the Research Gate portal.

In view of the above, I am asking you the following questions:

- Why SWOT analysis is one of the most commonly used research methods to analyze the functioning and development perspectives of a company?

- Is SWOT analysis an important element of the assessment process of strategic development opportunities for innovative startups?

- What types of research and research processes provide good data for SWOT analysis?

- Can sentiment analysis carried out on data obtained from the Internet be helpful for SWOT analysis?

- Can analytics based on Big Data Analytics help to carry out SWOT analysis?

- What do you think about this topic?

- What is your opinion on this topic?

Please reply.

I invite you to discussion.

Thank you very much.

Best wishes.

Dariusz Prokopowicz

Dear François Brault, Rivira Yuana, Michael Neubert

Thank you very much and best regards, Have a nice day,

Dariusz Prokopowicz

Stock price swings big when guidance is not met (profit warnings) or when profits exceed expectations. Forecasting in the age of BI and Big Data will leave the world of black magic and will enable better forecasting for managers and stock markets alike...