Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Harnessing Large Language Models for Enhanced Business Analytics

Harnessing Large Language Models for Enhanced Business Analytics

Marzullo, Fabio Perez

Paperback

ApplicationsGeneral ComputersProgramming

ISBN13: 9798369366912
Publisher: Igi Global Scientific Publishing
Published: May 20 2026
Pages: 372
Weight: 1.42
Height: 0.77 Width: 7.00 Depth: 10.00
Language: English
Harnessing large language models (LLMs) for enhanced business analytics changes how organizations process, interpret, and use data. These advanced AI systems utilize natural language understanding and generation, making them powerful tools for insights from data sources such as customer feedback, social media, emails, and reports. By integrating LLMs into business analytics workflows, companies can automate data interpretation, generate real-time insights, and support more informed decision-making. From summarizing complex datasets to predicting market trends and optimizing operations, LLMs redefine how businesses can analyze and leverage information, driving innovation and competitive advantage in a data-driven world. Harnessing Large Language Models for Enhanced Business Analytics delves into the transformative role of large language models (LLMs) in business analytics, bridging the gap between AI research and practical business applications by showcasing how LLMs can analyze datasets, uncover insights, predict trends, and facilitate decision-making. It examines theoretical foundations, practical applications, and future directions of LLMs in business environments. This book covers topics such as risk management, fraud detection, and data science, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and scientists.

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