Yes... Since 2003, big data has received extensive attention. The application of big data not only provides a lot of data foundation for industrial economic analysis, but also greatly enriches the methods of industrial economic data analysis, which greatly improves its precision and timeliness. While enjoying the convenience of using big data, it has also brought us major opportunities and challenges in many aspects, such as data purification, platform development, and personnel training. Big data technologies, such as college collections and multiple storage methods, can make good use of data in industrial economic statistics and forecasting. It enables related enterprises to build a set of real-time monitoring and energy-saving industrial big data management systems to provide more reliable data support.... Tan, L. (2020, April). Application of Big Data Technology in Industrial Economic Statistics and Forecasting. In 2020 International Conference on E-Commerce and Internet Technology (ECIT) (pp. 85-89). IEEE.

In fact. BI and Big Data should contribute to analyse the economic behavior of society but, I think exists a latent problem about the qualitative data, such us percpections and language semantic. How this practices could help to understand he market and economicsIn fact. BI and Big Data should contribute to analyse the economic behavior of society but, I think exists a latent problem about the qualitative data, such us percpections and semantic language. ¿How this practices could help to understand he market and economics?

Hi ,

the Business Intelligence and Big Data systems have considerably changed the possibilities for improving economic analysis and reducing decision-making time by using fact-based support systems.

The market practices, to apply in the improve business activities and timely decision making by using fact-based support systems. Based on this achieved operational performance and the economic growth..

Best Wishes..

Yes, Of course. With the improvements in Big Data analytics frameworks and techniques you can do analysis easily than before. Some advantages are,

• easy set up
• efficiency
• robustness
• fast learning
• lot of functionality to choose for graphs and so on
• lot of free libraries

Examples can be Spark and Jupyter notebooks. Data analysis with huge data has become affordable for many people because of these technologies.

I partially agree with you because my point of view is that the data is the gold, while big data and bi are tools for analyzing them. However, let me introduce a new perspective related to the kind of economical analysis and the decision making that we can do with them...what about the real-time decision making in stock markets? Big data is oriented to batch processing, while data stream engines are focused on the data processing on the fly. We have alternatives such as apache sparķ, storm, etc which allow articulating both contexts. Even more, the IoT environment is providing a new perspective for business in relation to the data gathering. I personally think that The Big Data, IoT and data streaming are key assets for fostering businesses, acting as a social and economical glue.

Dear Colleagues and Friends from RG,

In recent years, The Financial Industry 4.0 has grown in importance in business, economic and financial analytics, carried out on large quantitative data sets obtained from conducted research, and in predictive analyzes to determine the likely development of enterprises and institutions in subsequent years. ICT and Industry 4.0 information technologies are increasingly being implemented in business intelligence, to conduct Business intelligence type analyzes and research processes conducted on Big Data Analytics analytical platforms to support and improve business entity management processes. In recent years, new ICT information technologies, internet technologies and advanced data processing technologies Industry 4.0 have been used in many areas of economics, finance, banking, management, marketing, etc. The multi-faceted, functional and technological synergy of the development of these fields leads to the development of applications of ICT information technologies etc. in the field of advanced quantitative analyzes referred to as The Financial Industry 4.0 in economic and financial issues. In addition, the development of applications of The Financial Industry 4.0 in economic and financial analytics is one of the features of the development of modern knowledge-based economies. Technological progress in this issue is also an important attribute of comparative advantage between individual entities operating in the commercial financial sector. Therefore, improving the techniques of developing the applications of The Financial Industry 4.0 in economic and financial analytics becomes an important factor of competition between banks and other financial sector institutions in which financial risk management processes are a key issue for generating revenue from sales of financial products offered. In addition, the development of applications of The Financial Industry 4.0 in economic and financial analytics can significantly contribute to the improvement of system credit risk management processes in central institutions of the commercial and public financial system of the state, i.e. in central banking.

The multifactorial complex The Financial Industry 4.0 are also used to analyze quantitative results of scientific research. Correctly implemented econometric methods allow for objective processing of large quantitative data sets, thanks to which research theses are verified. The use of ICT information technology for the needs of econometric and statistical analytics allows for automation, standardization, objectification of carried out verification processes of quantitative data describing complex processes, etc. and reduction of the costs of analyzes. The computerized processes of using econometric and statistical tools for analyzing large quantitative data sets have enabled the development of analytics based on the use of advanced data processing technology Industry 4.0, including data processing in the cloud, in Big Data database systems, the use of Business Intelligence analytical platforms, the Internet of Things technology learning machines, artificial intelligence etc. Without statistical methods, it was not possible to effectively develop advanced Data Analytics, Data Science, etc. advanced analytics. Therefore, without the use of complex econometric models in verification processes and the analysis of large quantitative data sets, the development of scientific research would be much slower. than proceeding.

The Financial Industry 4.0 is particularly helpful in building complex, multifactorial models describing the functioning of complex economic organizations. An example is Business Intelligence analytics based on data from one side of the financial statements from previous periods and from data describing the current market situation and other aspects of the enterprise environment. In the Busines Intelligence computerized analytical platforms, The Financial Industry 4.0 is built by combining the formulas of economic and financial indicators, taking into account the mutual correlations and relationships between specific economic and financial categories that describe the functioning of a given entity, examined from previous studies. These correlations may relate, for example, to the impact of changes in the market environment on revenues from the sale of products or services. Changes in sales correlate with the efficiency of using fixed and working capital, with the level of debt, profitability, with the possibility of generating equity for further investments, etc.

In recent years, the application of Financial Industry 4.0, Business Intelligence, Data Science, Data Analytics, Big Data in the field of fundamental and technical analyzes carried out to examine future trends in the capital markets, including securities markets, has been growing. The Financial Industry 4.0 on the basis of this type of models allows on the basis of historical data, e.g. quantitative data contained in the financial statements of economic entities describing the economic condition and financial effectiveness of a specific company or institution to carry out predictive analyzes of the most likely extrapolation of the development trends of a given entity in correlation with specific factors market, economic and financial environment in order to prepare development forecasts for the specific economic entity surveyed in subsequent years. The multifactorial complex The Financial Industry 4.0 are also used, among others, for the forecast valuation of securities and other capital assets valued on the stock exchanges, commodity exchanges, currency markets and others. The multifactorial complex The Financial Industry 4.0 are also used to estimate the forecast level of stock indexes, to carry out fundamental analysis of securities issuers, forecasts of the development of financial markets, the likelihood of the emergence of the next financial and economic crisis.

In view of the above, business entity management processes are increasingly supported by computerized Business Intelligence platforms that facilitate multi-criteria analysis and reporting. This reporting would not have been possible without the use of complex econometric models whose formulas are entered in computerized analytical platforms. Complex, multi-criteria analyzes carried out using complex econometric models for verifying the operations of large companies require aggregation and analytical processing of large data sets in Big Data database systems. Specialized IT companies produce applications helpful in conducting economic analyzes, i.e. the Business Intelligence platform. Increasingly, large and medium-sized companies use these platforms adapting them to the specifics of their business. In connection with the above, the effective application and continuous improvement of certain complex, multifactorial econometric models used in Business Intelligence, Data Analytics, Data Science, Big Data Analytics, etc., significantly supports organization management processes and by using statistical methods also allows the development of various types of analysis predictive.

I conduct research in this area. I described the above issues in scientific publications that are available on the Research Gate portal. I invite you to cooperation.

Do you agree with me on the above matter?

In the context of the above discussion, I ask the following questions:

- Is The Financial Industry 4.0 growing in business, economic and financial analytics, as well as in predictive analyzes of determining the development of enterprises and institutions in the coming years?

- In connection with the development of Financial Industry 4.0 and Business Intelligence, Data Science, Data Analytics, Big Data, etc., will the level of precision of determining future development trends in the scope of fundamental and technical analyzes carried out to investigate the development of the situation and future trends be shaped in capital markets, including stock markets?

- What are the main determinants of the development of The Financial Industry 4.0?

Please reply

What do you think about this topic?

What is your opinion on this topic?

I invite you to discussion

Thank you very much

Best wishes

Dariusz Prokopowicz

Dear Juan Pablo Vazquez, C K Gomathy, Himesha Wijekoon, Aparna Kumari

Dariusz Prokopowicz

I say "yes". The synergy between the two is likely to improve the economic analysis.

Yes, BI and Big Data fusion can improve the financial analysis. As sales and Inventory analytics, Emerging Risk analysis, Fraud detection, real time analytics, Customer behavior, and recommendation analytics can directly impact the Financial analytics.

Dear Arbind K. Choudhary, Madhu Sharma Gaur, Dear Colleagues and Friends from RG, Thank you for the information provided and the link to interesting data in the above-mentioned issues. Thank you very much for participating in this discussion and for providing inspiring and informative responses. Thank you very much for the answers to the question: Does the combination of Big Data technology and Business Intelligence analytics make it possible to improve economic analysis? Thank you very much for the sent suggestions of interesting topics, research issues, etc. related to this issue. The issue is indeed developmental. Your statements confirm that the above-mentioned issues are current and developing.

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

Dariusz Prokopowicz

Its my Pleasure Sir, Dariusz Prokopowicz interesting combination

,

Dear Madhu Sharma Gaur, Thank you and invite you to the discussion. Best wishes,

Have a nice day,

Dariusz Prokopowicz

Interested

Yes... Since 2003, big data has received extensive attention. The application of big data not only provides a lot of data foundation for industrial economic analysis, but also greatly enriches the methods of industrial economic data analysis, which greatly improves its precision and timeliness. While enjoying the convenience of using big data, it has also brought us major opportunities and challenges in many aspects, such as data purification, platform development, and personnel training. Big data technologies, such as college collections and multiple storage methods, can make good use of data in industrial economic statistics and forecasting. It enables related enterprises to build a set of real-time monitoring and energy-saving industrial big data management systems to provide more reliable data support.... Tan, L. (2020, April). Application of Big Data Technology in Industrial Economic Statistics and Forecasting. In 2020 International Conference on E-Commerce and Internet Technology (ECIT) (pp. 85-89). IEEE.

Following article analyzes and discusses various applications and implications of Big Data for demo-economic analysis, focusing on the analysis of cell-phone data collected by telecommunication operators for billing purposes, commonly referred to as call-detail records… Letouzé, E. F. (2016). Applications and Implications of Big Data for Demo-Economic Analysis: The Case of Call-Detail Records (Doctoral dissertation, UC Berkeley).

BI usage... study is aimed at identifying the basics for integrating and adapting the world-wide experience of using business intelligence solutions (Business Intelligence, BI) for the business entities’ economic performance analysis in order to optimize this domain in the Russian environment for various purposes, including elaboration of an information quality improvement program and development of corporate-wide business intelligence systems... Mitrovic, S. (2020). Adapting of International Practices of Using Business-Intelligence to the Economic Analysis in Russia. In Digital Transformation of the Economy: Challenges, Trends and New Opportunities (pp. 129-139). Springer, Cham.

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Article Big data analytics capability and co-innovation: An empirical study

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