Leveraging large language model for enhanced business analytics on AWS
Mohajeri, Mahdiyeh Alsadat (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024052817328
https://urn.fi/URN:NBN:fi:amk-2024052817328
Tiivistelmä
In collaboration with one firm involved in the fast fashion world, the current research formed part of an exploratory research project. The project looked at how advanced cloud computing services and Large Language Models (LLMs) could be used to facilitate improvements in business analytics and the overall decision-making framework. The specific intention was to assess the features and roles of cloud platforms, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure, in the effective implementation of LLM within business analytics environments and further analysis of the effect of the utilization on data-driven decision-making.
The current theoretical framework was based on contemporary literature on big data analytics, cloud computing, and artificial intelligence. It has underlined exponential data generation and the resultant challenges in data management, strategic implications of cloud services in answering these challenges, and the transformational role of LLMs in processing and extracting actionable insights from massive datasets.
The study was methodologically rigorous in its multi-phase approach, including data preparation and pre-processing, feature extraction, and, most importantly, the phase of text analysis using Amazon SageMaker. This is a pointer to one of the resources by AWS, used in managing and scaling up deployments of models for machine learning, while Azure and GCP performance and security offerings are equally critiqued.
The results have shown AWS's outstanding ability to offer a wide range of services that may cover all analytical needs of an enterprise, which means that a company does not need to use other cloud services. This made AWS the choice of the company, as it facilitates the many functions without having to change between different services. This has made AWS the choice of the company, as it accommodates the many functions without necessarily needing to change between different services. This has made AWS the choice of.
In summary, the research was able to establish that AWS is a leader when it comes to the number of services offered and reliability and the aspect of scalability with a cloud service provider, especially for businesses that seek to leverage cloud computing to enjoy the full suite of benefits it offers businesses and LLMs. The strengths of GCP in data analytics, together with the open-source technology of Azure and massive integration it has with the ecosystem of Microsoft, are, in addition, the invaluable entryways given to businesses. However, AWS' complete ecosystem finally merges into a more consistent and streamlined cloud computing approach—one that can prove robust for operational efficiency and strategic agility in data-driven enterprises.
The current theoretical framework was based on contemporary literature on big data analytics, cloud computing, and artificial intelligence. It has underlined exponential data generation and the resultant challenges in data management, strategic implications of cloud services in answering these challenges, and the transformational role of LLMs in processing and extracting actionable insights from massive datasets.
The study was methodologically rigorous in its multi-phase approach, including data preparation and pre-processing, feature extraction, and, most importantly, the phase of text analysis using Amazon SageMaker. This is a pointer to one of the resources by AWS, used in managing and scaling up deployments of models for machine learning, while Azure and GCP performance and security offerings are equally critiqued.
The results have shown AWS's outstanding ability to offer a wide range of services that may cover all analytical needs of an enterprise, which means that a company does not need to use other cloud services. This made AWS the choice of the company, as it facilitates the many functions without having to change between different services. This has made AWS the choice of the company, as it accommodates the many functions without necessarily needing to change between different services. This has made AWS the choice of.
In summary, the research was able to establish that AWS is a leader when it comes to the number of services offered and reliability and the aspect of scalability with a cloud service provider, especially for businesses that seek to leverage cloud computing to enjoy the full suite of benefits it offers businesses and LLMs. The strengths of GCP in data analytics, together with the open-source technology of Azure and massive integration it has with the ecosystem of Microsoft, are, in addition, the invaluable entryways given to businesses. However, AWS' complete ecosystem finally merges into a more consistent and streamlined cloud computing approach—one that can prove robust for operational efficiency and strategic agility in data-driven enterprises.