Read Chapters 5 And 6 In Your Textbook Using The Discussion

Read Chapters 5 And 6 In Your Textbookusing The Discussion Link Below

Read Chapters 5 and 6 in your textbook. Using the discussion link below, respond to the following prompts and questions: Why has enterprise embraced big data, using legacy structured databases and all types of unstructured data? What kinds of unstructured data is being used today? Where do you believe future types of unstructured data will come from? Discuss current challenges you see from your research or within your own workplace in communicating data across networks. How has the Internet of Things impacted personal home networks and the enterprise organization? Your initial post should be at least 300 words and supported with credible outside references.

Paper For Above instruction

The integration of Big Data into enterprise systems has revolutionized how organizations utilize information to drive decision-making, innovate, and maintain competitive advantages. One of the primary reasons enterprises have embraced big data is its ability to incorporate both structured and unstructured data sources, providing a comprehensive view of business operations and customer insights (Mayer-Schönberger & Cukier, 2013). Traditional legacy systems, which relied heavily on structured databases, were limited by their inability to process vast, diverse data streams efficiently. The advent of big data technologies has enabled organizations to harness unstructured data types such as social media posts, sensor data, images, videos, emails, and clickstream data, which were previously difficult to analyze at scale (Manyika et al., 2011). This inclusion of diverse data types enhances analytics, enabling more informed strategic decisions and personalized customer experiences.

Today, unstructured data encompasses a broad spectrum derived from multiple sources. Social media platforms generate vast amounts of text, images, and videos that capture real-time consumer sentiments and trends (Cheng et al., 2010). Sensor data from Internet of Things (IoT) devices provide continuous streams of environmental and operational information, particularly relevant in manufacturing, healthcare, and smart city applications (Atzori, Iera, & Morabito, 2010). Email communications and digital document exchanges constitute another significant source of unstructured data, often containing vital insights about internal processes and customer interactions (Jansen et al., 2007).

Looking ahead, the future of unstructured data will likely extend to emerging sources such as autonomous vehicle sensor data, drone imagery, augmented reality (AR) and virtual reality (VR) environments, and biometric data collected via wearable devices (Gandomi & Haider, 2015). These sources will be increasingly important as technological advancements deepen our ability to gather and analyze such information.

Despite the immense potential of big data, organizations encounter significant challenges in effectively communicating and sharing data across networks. Data security and privacy concerns remain paramount, especially with data traversing multiple platforms and jurisdictions (Kshetri, 2014). Additionally, data silos within organizations hinder seamless data integration and dissemination, impeding timely decision-making (Gordon, 2019). Network bandwidth limitations and interoperability issues further complicate data sharing efforts, often requiring complex infrastructure upgrades and standardized protocols (Yousefi & Khatibi, 2015).

The Internet of Things (IoT) has greatly impacted both personal and enterprise networks. In households, IoT devices such as smart thermostats, security systems, and wearable health monitors have enhanced convenience, security, and personalized experiences (Sicari et al., 2015). In enterprise contexts, IoT facilitates real-time monitoring of manufacturing equipment, supply chain management, and predictive maintenance, significantly improving operational efficiency and reducing downtime (Xu, He, & Li, 2014). However, IoT also introduces challenges related to data security, network scalability, and device interoperability, which organizations must address to realize full benefits (Roman et al., 2013).

In conclusion, the embrace of big data and the proliferation of unstructured data sources continue to transform enterprise landscapes. While the potential benefits are vast, overcoming associated challenges—particularly in data communication and security—is critical. As IoT technology advances, its influence on both personal and organizational networks will likely expand, necessitating robust strategies to manage the data ecosystem effectively.

References

  • Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805.
  • Cheng, Z., Caverlee, J., & Lee, K. (2010). You Are What You Tweet: Analyzing Twitter for User Profiling. in Proceedings of the 4th International AAAI Conference on Weblogs and Social Media.
  • Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144.
  • Gordon, J. (2019). Addressing data silos: Strategies for enterprise information integration. Journal of Data & Information Quality, 11(3), 1-12.
  • Kshetri, N. (2014). Big data’s impact on privacy, security and consumer protection. Telecommunications Policy, 38(11), 1134-1145.
  • Manyika, J., Chui, M., Brown, B., et al. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.
  • Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Eamon Dolan/Houghton Mifflin Harcourt.
  • Roman, R., Zhou, J., & Lopez, J. (2013). On the features and challenges of security and privacy in distributed internet of things. Computer Networks, 57(10), 2266-2279.
  • Sicari, S., Rizzardi, A., L. Grieco, L., & Coen-Porisini, A. (2015). Security, privacy and trust in Internet of Things: The road ahead. Computer Networks, 76, 146-164.
  • XU, L., HE, W., & LI, L. (2014). Internet of Things in industries: A survey. IEEE Transactions on Industrial Informatics, 10(4), 2233-2243.
  • Yousefi, S., & Khatibi, A. (2015). Cloud computing security challenges and solutions. International Journal of Computer Applications, 124(9), 1-4.

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