Big data analytics (BDA) is a major paradigm shift in business analytics. Big data refers primarily to datasets which are characterized by what some authors term the “three Vs” or volume, variety, and velocity. By this, it is meant that first of all, big data is big, with the total amount of data totaling in the terabytes or petabytes. Big data is also typically unstructured and highly heterogeneous, rather than fixed into a single structured format. Business organizations often do not get proper analysis required for value generation from their big data resources, largely due to misunderstanding of big data resources or poor integration of BDA tools into the decision making processes.
Papers:
S. F. Wamba. A. Gunasekaran. S. Akter. S. J. Ren. R. Dubey and S. J. Childe. “Big data analytic and firm performance: Effects of dynamic capabilities”. Journal of Business Research, vol. 70, pp. 356-365. 2017.
U. Sivarajah, M. M. Kamal, Z. Irani and V. Weerakkody. “Critical analysis of Big Data challenges and analytical methods”. Journal of Business Research, 70, 263-286. 2017.
W. A. Günther, M. H. Rezazade Mehrizi, M. Huysman and F. Feldsberg. “Debating big data: A literature review on realizing value from big data”. Journal of Strategic Information Systems, vol. 26, pp. 191-209. 2017.
A. Gandomi and M. Haider. “Beyond the hype: Big data concepts, methods and analytics”. International Journal of Information Management, vol. 35, pp. 137-144. 2015.
From a practical sense, all customer metrics should align with sales revenue growth and enterprise financial statements. At least one of the above sources do not align with this principle (too abstract).
Hi.,
Businesses and Big Data Analytics:These tools help in providing meaningful information for making better business decisions. The companies can improve their strategies by keeping in mind the customer focus. Big data analytics efficiently helps operations to become more effective.
The capabilities are critical to turning data into insight.
- Business alignment. ...
- Data understanding. ...
- Data quality. ...
- Data-centric processes. ...
- Data-centric resources.
- The three keys to creating a successful analytics program are:
- 1) obtain strong executive understanding and support
- 2) deliver quick, meaningful business wins
- 3) make one person and group accountable for the program.
Organizational success is the result of multiple variables, including the utilization of big data in decision making, such as customer relationships. The organization has to identify the specific area where data analytics will be used for implementing a customer relationship strategy and measure the performance within a particular area to determine the success of the strategy based on the BDA. Thanks.
Dear Colleagues and Friends from RG, In recent years, the scope of applications of Big Data technology and Data Science and Data Analytics 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 the 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 particularly dynamically developing and are used in knowledge-based economies. 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. In connection with the above, it has been growing in recent years, and will increase in the coming years, 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 the management of organization processes in various aspects of operations, including also in terms of improving customer relationships. 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.
Best wishes
Dariusz Prokopowicz
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