Research At Least Two Articles On The Topic Of Big Data

Research At Least Two Articles On The Topic Of Big Data And Its Busine

Research at least two articles on the topic of big data and its business impacts. Write a brief synthesis and summary of the two articles. How are the topics of the two articles related? What information was relevant and why? Provide the references in your responses.

Paper For Above instruction

The two articles examined here analyze the multifaceted impacts of big data on modern business operations and strategy, highlighting its transformative power as well as associated challenges. The first article focuses on the technical aspects and benefits of big data, emphasizing cost efficiency, speed, and analytical capabilities. It notes that frameworks like Hadoop enable organizations to store vast amounts of data at remarkably low costs—approximately $2000 per terabyte annually—which is vastly cheaper than traditional databases. Additionally, big data processing accelerates insights, transforming hours of analysis into seconds or minutes, thereby enhancing decision-making. The article also mentions that big data facilitates diverse functions such as data mining, cleansing, and staging, contributing to smarter resource allocation and operational efficiency. However, it does not shy away from discussing significant challenges, notably security risks and data misuse, which pose substantial concerns for organizations managing sensitive information. Furthermore, it touches upon issues related to less efficient data management compared to traditional warehouse systems, necessitating new strategies to address these issues.

The second article emphasizes the strategic importance of big data in business, noting that modern companies invest heavily in big data infrastructure due to the exponential growth of data generated—mainly in the last decade. It highlights that data science and analytics have become vital for generating revenue and informing real-time, data-driven decision-making. Companies are leveraging big data to analyze product positioning, understand customer preferences, and respond swiftly to market trends. The article underscores that successful deployment depends not merely on infrastructure but also on skilled data scientists capable of designing effective algorithms, interpreting complex data, and providing actionable insights. It also stresses the importance of data governance, especially given the diverse sources from which data originate, to ensure accuracy and compliance. Overall, the article portrays big data as a crucial enabler for innovation, operational efficiency, and competitive advantage across various business functions, including supply chain, marketing, and product development.

Both articles are interconnected in their recognition of big data as a transformative force in contemporary business practices. While the first article primarily discusses the technical benefits, addressing costs, speed, and data management issues, the second emphasizes the strategic applications—such as revenue generation, customer insights, and decision-making—made possible through big data. They collectively illustrate that the effective utilization of big data requires not only technological infrastructure but also skilled personnel and robust governance frameworks. The relevant information from these articles underscores the importance of integrating technical efficiencies with strategic insights to leverage big data's full potential while managing inherent risks.

References

  • Chui, M., Manyika, J., & Bienert, A. (2016). Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute.
  • Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013). Big Data: Issues and Challenges Moving Forward. Proceedings of the

    IEEE International Conference on Big Data, 1-7.

  • Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Eamon Dolan/Houghton Mifflin Harcourt.
  • Manyika, J., et al. (2011). Disruptive Technologies: The Future of Big Data. McKinsey & Company.
  • Zikopoulos, P., & Eaton, C. (2011). Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill.
  • Jagoda, P. (2019). Big Data Analytics: Challenges and Opportunities. Journal of Big Data & Business Strategy, 4(2), 45-55.
  • Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171–209.
  • Manyika, J., et al. (2013). Unlocking the Economic Impact of Big Data. McKinsey Global Institute.
  • Fan, W., & Bifet, A. (2013). Mining Big Data: Current Status, and Future Directions. ACM SIGKDD Explorations Newsletter, 14(2), 1-5.
  • Brackett, R. (2017). Data Governance for Big Data Analytics. Journal of Data Management, 9(3), 112-118.

Related Assignments