The Big Data’ Significance for the Companies Essay

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Updated: Jan 6th, 2024

Abstract

The paper highlighted the significance of the big data due to its ability to enhance the strategy and create a distinct competitive advantage for the company. Nonetheless, the primary difficulty is the skill to classify and select only relevant sectors of information. In turn, the accessibility of the Internet, extreme usage of the social media, and availability of the Internet on different devices change the trends in business. These modifications affect the flow of business processes and revolutionize the perception towards marketing.

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The integrative, traditional, and intelligence methods are used to gather the information in the context of marketing and finances. In turn, the intelligence gathering could be considered as the most beneficial and innovative approach due to the rapidness, clarity of information, and the ability to control and modify the variables of search. The Internet is useful for the formation of the marketing trends due to the formulation of big data with the social networks, information transparency, and the creation of the user personas. In turn, the companies tend to respond to the variety of knowledge by utilizing innovative instruments such as cloud-computing technology, predictive analytics, and increased intensity of online security.

Main

Technology has a tendency to define the flow of the business processes while enhancing the availability of information. Big data’s relevance cannot be underestimated, as the organizations have to deal with high volumes of information daily to comply with the existing trends in the world. In this instance, big data can be utilized as a strategical instrument to maintain the company’s competitiveness on the high level (Rijmenam, 2014). Firstly, the big data provides an extensive range of opportunities for the business owners while offering the insight information about the particular areas of operation (Surdak, 2014). It is evident that the perceptions suggest the hints about the creation and development of the distinct competitive advantage to be noticeable among the competitors. Nonetheless, the primary difficulty is the capability to classify the sources of information correctly while paying attention only to the matters, which can affect the business substantially.

In turn, the cultural changes in technology, which revolutionize business today, currently influence the operations of various organizational entities. Nowadays, the main technological and cultural changes, which are related to the behavior of the user, can be formulated as the access to the Internet, activity in the social networks, and utilization of various devices to exchange information. All of these matters define the presence of the large volumes of data in free access. In turn, the integration of the Internet with the marketing activities contributes to the necessity to deliver information to the dissimilar consumer groups, and it has a high influence on the export and efficiency of the marketing due to the high accessibility of the Internet resources (Prasad, Ramamurthy, & Naidi, 2001). Furthermore, the popularity of the social networks has a similar influence, but it also contributes to the communication to the users and development of e-commerce due to the rapid technological innovation (Winter, 2012). As for the gadget, the businesses have to devote vehement attention to the research and development due to the necessity to create the applications to make the company visible in the smartphone’s world, and it modifies the flow of organizational processes (Weerakkody, Currie, & Ekanayake, 2003).

Furthermore, the methods of data collection and its utility is evaluated while applying these matters in the context of marketing and finance. In this instance, the integration is utilized for formulated the tendencies in marketing and financial sphere, as a combination of data sets contributes to the formation of the relevant perception of the current situation in the business field (Grandinetti & Kunze 2015). In turn, the intelligence gathering is actively used in the modern world (Pedrycz & Chen, 2014). This approach can be considered as the most popular technique due to its ability to adjust the criteria for the data collection. It is apparent this highly computerized engine will replace the traditional tools as it has an advantageous influence on the information maintenance and analysis and marketing in finance due to its rapidness, clarity, and ease of variables’ modifications while delivering the results.

The Internet can be considered as a relevant instrument due to the ability to gather an extended variety of facts and information considering various topics. It remains evident that the Internet is often used as a tool to collect the information and build the projections and assumptions about the particular trends in the business area. For instance, the information in the social networks contributes to the formation of big data, which can help analyze the existent preferences in the society (Chan, 2014). In turn, the companies can effortlessly learn about the strategies of the competitors and actions of customers due to the information transparency (Grandos, Gupta, & Kauffman, 2010). Finally, the Internet helps define the user personas, which represent the various behaviors of the consumer groups (Schafer, & Klammer, 2015).

Lastly, it will be determined how the companies tend to respond to the presented knowledge while utilizing innovative instruments. In this instance, cloud-computing technology is one of the approaches to the processing of the large volumes of information, which is available online (Pedrycz & Chen, 2014). In turn, predictive analytics are used in the banking industry to analyze large volumes of data, assume the potential trends of the industry, and minimize fraud (Conz & Rodier, 2007). Lastly, the companies have to pay attention to the online security, as, in this instance, it contributes to the establishment of the trusting relationships with the customers by assuring the safety of the connection and transactions (Roca, Garcia, & Vega, 2009). This restriction is a requirement in the banking and stock trading platforms.

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References

Chan, J. (2014). Big data customer knowledge management. Communications of IIMA, 14(3/4), 45-55.

Conz, N., & Rodier, M. (2007). The next big thing – Predictive analytics: Back to the future – Financial services companies are analyzing rising data volumes with predictive analytics to glimpse the future and segment consumers, build stronger customer relationships and reduce fraud. Insurance & Technology, 32(12), 27.

Grandinetti, L., & Kunze, J. (2015). Big data and high performance computing. Amsterdam, Netherlands: IOS Press.

Grandos, N., Gupta, A., & Kauffman, R. (2010). Information transparency in business-to-consumer markets: Concepts, framework, and research agenda. Information Systems Research, 21(2), 207-226.

Pedrycz, W., & Chen, S. (2014). Information granularity, big data, and computational intelligence. New York, NY: Springer.

Prasad, K., Ramamurthy, K., & Naidi, G. (2001). The influence of internet-marketing integration on marketing competences and export performance. Journal of International Marketing, 9(4), 82-110.

Rijmenam, M. (2014). Think bigger: Developing a successful big data strategy for your business. New York: AMACOM.

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Roca, J., Garcia, J., & Vega, J. (2009). The importance of perceived trust, security, and privacy in online trading systems. Information Management & Computer Security, 17(2), 96-113.

Schafer, A., & Klammer, J. (2015). Service-dominant logic in practice – using online customer communities and personas. Marketing Review St. Gallen, 32(5), 90-96.

Surdak, C. (2014). Data crush: How the information tidal wave is driving new business opportunities. New York: AMACOM.

Weerakkody, V., Currie, W., & Ekanayake, Y. (2003). Re-engineering business processes through application service providers: Challenges, issues, and complexities. Business Process Management Journal, 9(6), 776-794.

Winter, S. (2012). The rise of cyberinfrastructure and grand challenges for eCommerce. Information Systems and eBusiness Management, 10(3), 279-293.

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IvyPanda. 2024. "The Big Data' Significance for the Companies." January 6, 2024. https://ivypanda.com/essays/the-big-data-significance-for-the-companies/.

1. IvyPanda. "The Big Data' Significance for the Companies." January 6, 2024. https://ivypanda.com/essays/the-big-data-significance-for-the-companies/.


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