Economic Data Value for Business Decisions

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Although it is not easy to measure and quantify the value of statistics in modern society, the US government data plays fundamental roles in several sectors of the nation’s economy. According to Hughes-Cromwick and Coronado’s (2019) article on the value of economic data on business decisions, there are several benefits gained for the use of the database. The report provides a comprehensive analogy of the role of public good in shaping how both private and public institutions can utilize their data for beneficial purposes. Some of the major sectors evaluated in this manuscript include the energy segment, automotive industry, and financial services. The availability of public numbers about various statistics and finding within the market scope can significantly alter the way firms make their considerations about specific production approaches. Accordingly, the authors argue that with the new dominance in the virtual approach to data management, the federal agencies will find it very interesting to ensure that everyone is educated on business behavior and social behavior norms with the businesses.

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The developments in technology including big data have also resulted in consolidation of database for businesses around the globe. Zhao et al. (2016), in the article “Distributed feature selection for efficient economic big data analysis,” offers useful analysis about the role of data in business operations. The authors delve into the collection of economic data and how they are utilized in modern business operations to realize maximum profit. Accordingly, the process of collecting the data itself offers economic opportunities for the firms to invest in developing the big data system. The perspectives of econometrics play a fundamental role in the decision-making model as companies seek to appreciate the development of big data systems across the universe. Succinctly, the advent of big data technology shaped the approach to information mining in various sectors. At the same time, it may have a long-term effect on the operation models utilized by both the small entities and well-established market gurus. The article establishes that some of the critical attributes of economic data are not only on their accessibility but also on how well they can be manipulated to benefit companies in several sectors. Thus, there is a need to have an effective strategy of collecting and analyzing economic data to help firms evaluate their performances in an economy.

Almost all sectors consider real-time information to be important. The article by Ming et al. (2018) on “Analysis models of technical and economic data of mining enterprises based on big data analysis” further proves that the big data approach had become a significant business operation aspect. Based on their study, economic data has distinctive relevance in mining sectors’ sustainability like any other segment of the economy. Miners need to access the sales price data, fluctuation patterns alongside the big data technology’s analytical relevance to make decisions pivotal in their continued growth and development. Logically, the mining statistic and geological study findings will become very influential in establishing the viability of any market for minerals. Thus, the availability of such information on the government portals may become a significant blessing in many firms’ operations.

Other researchers focus on the value of facts and modern approaches enhance their managerial methodologies. Popovič et al. (2018) use the article “The impact of big data analytics on firms’ high value business performance” to explain the emerging trend in the big data approach to decision-making among companies worldwide. Their key objective is to explore the pragmatism of a big data system within the manufacturing sector. Notably, manufacturers require updated information setting to compete favorably within the industry. Thus, the technique utilizes capacity-building as a tool to ensure that they can have access to information and integrate the findings for proper planning.

Modern technocrats focus on both quantitative and qualitative approaches. The article “The Impact of Big Data on Business Management Decisions” by Yunpeng’ (2019) uses an analytical approach to understand big data systems’ implications on managerial decisions. The study focuses on various aspects of the new technology, highlighting types and meaning to create a fundamental background about this technology. Succinctly, they establish that all enterprises have witnessed massive transformation on how to make timely decisions. Primarily, the surge in technological know-how and the use of computers to generate various pieces of information saves time and money while approaching marketing challenges.

The technology has multiple benefits in organizational culture and development. Santoro et al. (2019) highlight the benefits of big data among retailers in “Big data for business management in the retail industry. Management Decision” The study reveals that analyzing data in the market using big data techniques can help change the direction of the market approach for prosperity among retailers. Thus, even entrepreneurs need to understand the value of knowledge gained from exposure and national resource centers to help them compete favorably within their market structures.

To conclude, these articles showcase that economic data is important in the sustainability of businesses around the globe. The government’s collection and centralization of such data to be accessed by different organizations save the firms a substantial amount in economic data mining. Therefore, as an emerging issue, big data analytics may have critical effects on companies’ future operations. The availability of a centralized government database to ease information retrieval and continuous development will enhance economic growth and development standards among different firms in the world. Nonetheless, the paradigm to technology-based data collection and storage will create a massive pool of resources and facts for factual and evidence-based decision-making among companies.

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Annotated Bibliography

Hughes-Cromwick, E., & Coronado, J. (2019). The value of US government data to US business decisions. Journal of Economic Perspectives, 33(1), 131-146.

The article is a qualitative report that provides evaluation results from the US government database. The main sectors evaluated include energy, automotive, and finance service whose key finding indicates that the centralized data system greatly improves the performance of organizations in several settings. One of the strengths is the choice of words and the subject focus, since the authors narrow down to manageable sample size of three industries to provide valid results.

Ming, J., Zhang, L., Sun, J., & Zhang, Y. (2018, April). Analysis models of technical and economic data of mining enterprises based on big data analysis. In 2018 IEEE 3rd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA) (pp. 224-227). IEEE.

The authors use economic variables, including sales and the use of technology for research in the mining sector to conduct a qualitative study about big data. They establish that big data technology can help in predicting the soil mineral endowment and capture the trends of production in the industry. The authors, notably, use technical analytical tools to help establish the scope of technology in the mining sector. However, the authors fail to highlight the key relation to data valuation and sampling design.

Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20(2), 209-222.

This study qualitatively investigates the implication of emerging big data analytics (BDA) in the manufacturing sector. They establish that BDA can influence the management and productivity culture in several. The key strength portrayed by the study is its sample of three companies, which time for valid data extraction. The authors use a simple qualitative approach to help the readers follow the findings easily.

Santoro, G., Fiano, F., Bertoldi, B., & Ciampi, F. (2019). Big data for business management in the retail industry. Management Decision, 57(8), 13.

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This article focuses on the retail setting and gathers information on how big data can shape their culture. The authors establish that the collection procedures, competence levels, and desire to share are the key concerns in data management. Focusing on retailers is a major contribution to the literature and provides an opportunity to understand the values of data in such a unique environment. Nonetheless, there are no defined sample sizes in the study to help highlight the representation of other businesses.

Yunpeng, L. (2019). The impact of big data on business management decisions. 2019 International Conference on Arts, Management, Education and Innovation (ICAMEI 2019).

The study focuses on big data application, problems faced, and how managers seize opportunities to utilize these systems. The researcher uses a cross-sectional survey to understand the value of big data in modern enterprise decision-making procedures. Although there is no vivid experimentation conducted, the author borrows from a theoretical perspective to explain the phenomenon. There is a need to understand the study motif and enable readers to comprehend the underlying issues.

Zhao, L., Chen, Z., Hu, Y., Min, G., & Jiang, Z. (2016). Distributed feature selection for efficient economic big data analysis. IEEE Transactions on Big Data, 4(2), 164-176.

The paper presents a model of addressing the challenges facing the analysis of economic data in various sectors of the economy. The key concepts include data processing, innovation, and models of analysis. Zhao et al. use the emerging trends in technology development to understand the disparities in data input within different firms. One notable weakness is the lack of appropriate research philosophy and sampling procedure. The conclusion will help in evaluating the recent challenges in business.

References

Hughes-Cromwick, E., & Coronado, J. (2019). The value of US government data to US business decisions. Journal of Economic Perspectives, 33(1), 131-46. Web.

Ming, J., Zhang, L., Sun, J., & Zhang, Y. (2018, April). Analysis models of technical and economic data of mining enterprises based on big data analysis. In 2018 IEEE 3rd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA) (pp. 224-227). IEEE.

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Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20(2), 209-222.

Santoro, G., Fiano, F., Bertoldi, B., & Ciampi, F. (2019). Big data for business management in the retail industry. Management Decision, 57(8), 13.

Yunpeng, L. (2019). The impact of big data on business management decisions. 2019 International Conference on Arts, Management, Education and Innovation (ICAMEI 2019). Web.

Zhao, L., Chen, Z., Hu, Y., Min, G., & Jiang, Z. (2016). Distributed feature selection for efficient economic big data analysis. IEEE Transactions on Big Data, 4(2), 164-176. Web.

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BusinessEssay. 2022. "Economic Data Value for Business Decisions." February 24, 2022. https://business-essay.com/economic-data-value-for-business-decisions/.

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