INTROUDCTION
Current and future challenges in big data analytics involve making big data obtainable, upholding quality data, keeping the data protected and recognising the right platforms and tools (Naeem, et al. 2022). This report will imitate on the findings of assessment one to analyse the present and future challenges within big data analytics which might hamper ability of an organization to attain its objectives.
MAIN BODY
Reflection of big data challenges and organisational goals
In the assessment one, I have overseen the application of big data to assist business objectives and activities of Amazon, and also analysed the different types of information systems and suggestions for information systems suitable for Amazon. Although big data has its advantages, such as improved customer experiences, better business operations, and innovation, it also represents a set of challenges. Within this reflection, I will follow the Gibbs reflective model to gauge the present and upcoming challenges in big data analysis which might hamper ability of an organization to attain its business objectives. Gibbs reflective cycle is an organized outline developed to direct people while performing the reflective process about past experiences in a structured manner. Such cycle is made of six stages which are, description; feelings; evaluation; analysis; conclusion and action plan (Galli, and New, 2022).
As Amazon is an international e-retailer, it depends very much on big data for managing its logistics and supply chain, uncovering frauds, customising experiences of its customers and also for fostering innovation. The organization gathers large volumes of data on day-to-day basis through behaviour of customer, transactions and reviews of products on website. But, working with vast amount of data comes up with numerous challenges, which involve upholding quality of information and data, processing volume or capacity, and data privacy and security (Tableau. 2025). Despite the significant benefits, problems such as concerns related to confidentiality and privacy, complications in implementation and danger of imprecise evaluation remains protuberant.
While taking into account the application of big data within business process and activities of Amazon, I felt like the company has taken substantial steps in exploiting data to improve the business activities and experiences of its customers. Though, the challenges related to big data which might hamper the company’s development, make me feel worried. Regardless of the great potential, if these challenges are not considered appropriately, it might lead to struggles for the company in attaining business objectives. As the company gathers big volumes of confidential data from its customers or users, I think confirming data privacy and security should be the primary concern at the company. As this can lead to dangers of data violation, misapplication of user data and information and also hacking. As per my views, these problems can result into lack of faith of customer on the brand, impacting the brand image and loyalty of customers towards the company (Himeur, et al. 2023). Even though determination to execute risk handling plans and security measure, there persists the risk of hacks and cyber-attacks.
Moreover, the company functions through many channels worldwide, incorporating data from diverse bases for guaranteeing preciseness, pertinences and constancy can be an issues. Such vast data from numerous channels could result into discrepancies as well as improper analysis of data, in case of not managing data appropriately. In addition, another challenge which I observed while working on the assessment one, has been upholding great quality, precise data. Poor and unclear data can result into inexact perceptions, which in turn can result untrue forecasts, or wrong decision in chief domains (Rani, et al. 2023). Moreover, as the company grows, the amount of data it produces also rises, because of this they may deal with issues in scaling up in an effective manner.
I have understood that if the data is compromised at any cost, it can result into financial and legal consequences and even shatter the company’s image. When the customers are unwilling to share their data, due to fear of data getting exposed, this can result into complication of the capability of Amazon to adhere with the data protection rules such as GDPR. This in turn put more pressure on the organization in order uphold strong security protocols. Furthermore, due to large amounts of data, confirming that each and every point of data is exact and precise, is also an issue (Al-Sartawi, 2021). Inexact data can even result into deprived decision making processes in relation to marketing plans, inventory management, or product launches.
Further, as per the evaluation I have done, complexity of incorporating different data bases generates blockages in process of decision making. For example, data from diverse fulfilment epicentres is not lined up, it can result in excess inventory or stock out, which impact the business’s operational competence. Moreover, without appropriate infrastructure, technologies and tools processing wide data volumes, there is a risk of postponements in offering perceptions, slowing down process of decision making and impacting operational competence (Ogbuke, et al. 2022) Due to this, the company might find it tough to uphold competitive advantage in the market.
In conclusion, I have learned a lot about the benefits and challenges of big data integration and also the way it impacts large companies like Amazon. Further, initially I felt that the integration of big data comes up with a lot of benefits and such benefits overweigh the challenges of integration of big data. But, through reflection on challenges and critical evaluation, I learned that there are a lot of challenges in the incorporation of big data analysis and they need to be addressed. Thus, now the businesses will be able to operate effectively as they comply with the effective type of the big data. If the large organisation can not consider these challenges, they might deal with disturbances in its business operations, damage to faith of customer towards brand and inadequacies in the procedure of decision making.
While working on this assessment, I have understood that I need to improve my researching skills and also critical thinking skills. To improve researching skills, I will enrol in an online course which will help me to learn advanced search skills. I will use online resources like online websites offering such courses and videos, and accomplish this goal in 6 months. Further, I will develop advance critical thinking skills by using wasted time, solving one problem every day, internalizing intellectual norms, and keeping an intellectual journal. In addition, I will be using online resources like e-books, articles and journals, and develop such abilities in 5 months.
CONCLUSION
On the basis of above study, it can be concluded that big data management is crucial because it offers improved decision-making, which ultimately helps the organisations like Amazon to attain their organisational goals. This report has reflected on the challenges of big data analytics which has been evaluated in assessment one.
If structuring reflections, applying academic models, or maintaining clarity feels difficult, professional assignment help can refine your analysis, improve coherence, and ensure academic standards are met confidently.
REFERENCES
Books and Journals
Al-Sartawi, M., 2021. Big data-driven digital economy: artificial and computational intelligence (Vol. 974). Cham: Springer.
Bassot, B., 2024. The reflective journal. Bloomsbury Publishing.
Galli, F. and New, K.J., 2022. Gibbs’ cycle review. Emotions as a part of the cycle. e-Motion: Revista de Educación, Motricidad e Investigación, (19), pp.92-101.
Himeur, Y., Elnour, M., Fadli, F., Meskin, N., Petri, I., Rezgui, Y., Bensaali, F. and Amira, A., 2023. AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives. Artificial Intelligence Review, 56(6), pp.4929-5021.
Naeem, M., Jamal, T., Diaz-Martinez, J., Butt, S.A., Montesano, N., Tariq, M.I., De-la-Hoz-Franco, E. and De-La-Hoz-Valdiris, E., 2022. Trends and future perspective challenges in big data. In Advances in intelligent data analysis and applications: Proceeding of the sixth euro-China conference on intelligent data analysis and applications, 15–18 October 2019, Arad, Romania (pp. 309-325). Springer Singapore.
Ogbuke, N.J., Yusuf, Y.Y., Dharma, K. and Mercangoz, B.A., 2022. Big data supply chain analytics: ethical, privacy and security challenges posed to business, industries and society. Production Planning & Control, 33(2-3), pp.123-137.
Rani, S., Bhambri, P., Kataria, A., Khang, A. and Sivaraman, A.K. eds., 2023. Big Data, Cloud Computing and IoT: Tools and Applications. CRC Press.
Online
Tableau. 2025. Online. Available through: < https://www.tableau.com/analytics/what-is-big-data-analytics>
