The Purpose Of The Journal Entry Assignments In This Course

The Purpose Of The Journal Entry Assignments In This Course Is To Demo

The purpose of the journal entry assignments in this course is to demonstrate that you can link specific technologies to the business side, so it is essential that your analysis focuses on linking and synthesizing information learned in this course to the greater body of knowledge related to computer-based information systems. For this journal entry, you will analyze big data to explain what the technology is, why it is important, its business significance, and its social and/or ethical implications. To complete this journal entry, be sure to address the critical elements below, labeling each section as follows: Technology Definition: Describe the technology and its industry in a concise summary. Business Application(s): Explain the possible business applications of the technology, addressing the following questions: Why is this technology important or significant? How does the technology create value for businesses? What processes are improved, enhanced, or changed positively? Business/Society Implication: Assess the potential implications of this technology to businesses. Consider ethical and societal impacts. This section needs to be analytical rather than descriptive.

Paper For Above instruction

Big data has revolutionized the way organizations make decisions, innovate, and create value across industries. It refers to the vast volume of structured and unstructured data generated from various sources, including social media, sensors, transactions, and other digital platforms. The technology involves the collection, storage, and analysis of enormous data sets that traditional data processing software cannot handle efficiently. Big data analytics harnesses advanced algorithms, machine learning, and artificial intelligence to extract meaningful insights, predict trends, and inform strategic business actions (Mayer-Schönberger & Cukier, 2013). Its influence spans industries such as healthcare, finance, retail, manufacturing, and transportation, transforming how companies operate and compete in the digital age.

From a business perspective, big data offers numerous applications that generate significant value. One primary application is personalized marketing, where organizations analyze consumer data to tailor products, services, and advertising efforts to individual preferences. Retail giants like Amazon utilize big data analytics to recommend products based on customer behavior, increasing sales and customer loyalty (Chen, Chiang, & Storey, 2012). Additionally, big data enhances supply chain management by providing real-time insights into inventory levels, logistics, and supplier performance, leading to cost reductions and efficiency improvements (Fosso Wamba et al., 2015). In finance, big data enables risk assessment and fraud detection through pattern recognition and anomaly detection algorithms, contributing to more secure financial transactions. Moreover, predictive maintenance in manufacturing relies on sensor data to optimize equipment performance, minimize downtime, and reduce operational costs (Manyika et al., 2011).

The importance of big data in the business realm lies in its capacity to turn raw data into actionable insights, fostering data-driven decision-making that can lead to competitive advantages. Companies that leverage big data can anticipate market trends, better understand customer needs, and innovate faster than competitors relying on traditional data analysis methods. For example, healthcare providers analyze electronic health records and wearable device data to improve patient outcomes through personalized treatment plans. Similarly, in the transportation sector, ride-sharing companies analyze traffic and user data to optimize routes and supply chain logistics (McAfee et al., 2012). Furthermore, big data analytics supports strategic innovation initiatives, enabling organizations to explore new markets or develop new products based on emerging consumer behavior patterns.

Despite its business benefits, the adoption and use of big data raise significant ethical and social concerns. Privacy is a primary issue, as the collection and analysis of personal data can lead to infringements on individual rights if not managed properly (Tene & Polonetsky, 2013). Data security is also critical, especially with the increasing frequency of cyberattacks targeting sensitive information. Another concern pertains to bias and discrimination; algorithms trained on biased data may perpetuate social inequalities, resulting in unfair treatment of certain demographic groups (O’Neil, 2016). Furthermore, the societal implications of surveillance enabled by big data analytics can impact civil liberties and consumer trust. As such, organizations must implement ethical frameworks and transparent data governance policies to mitigate these risks. The social responsibility of organizations in leveraging big data involves ensuring privacy, promoting fairness, and maintaining accountability in their data practices, which is vital for sustainable and ethical growth in the digital economy.

References

• Chen, H., Chiang, R., & Storey, V. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.
• Fosso Wamba, S., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How 'big data' analytics can be used to improve supply chain management: A systematic review. International Journal of Production Research, 54(23), 7132-7151.
• Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt.
• Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.
• McAfee, A., Brynjolfsson, E., Davenport, T., Patil, D., & Barton, D. (2012). Big Data: The Management Revolution. Harvard Business Review, 90(10), 60-68.
• O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group.
• Tene, O., & Polonetsky, J. (2013). Big Data for All: Privacy and User Control in the Data-Driven World. North Carolina Law Review, 92, 1101-1134.