Business Analytics using Python (Paperback)

Lingua: inglese

Editore: Independently Published, 2024

9798300531072

Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

Venditore con 5 stelle

Venditore AbeBooks dal 12 ottobre 2005

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Paperback. In today's fast-paced and data-driven world, businesses are increasingly relying on data to guide their strategies, optimize operations, and stay ahead of the competition. From customer behavior to market trends, every facet of a business generates vast amounts of data-data that holds the key to better decision-making, enhanced performance, and greater profitability. However, unlocking the potential of this data requires more than just access to it; it requires the tools, techniques, and frameworks that allow us to analyze, interpret, and act on the insights it provides. This book, Business Analytics using Python: Practical Approaches to Data-Driven Decision Making, is designed to provide you with the knowledge and practical skills necessary to leverage the power of data in business contexts. Whether you are a business analyst, data scientist, or business manager, this book aims to equip you with a solid foundation in business analytics using Python, one of the most powerful and widely used open-source programming languages for statistical analysis and data science. Python has become an indispensable tool in the world of analytics. Its flexibility, vast library of packages, and user-friendly environment make it ideal for analyzing and visualizing data, building predictive models, and uncovering trends that drive business success. In this book, we will guide you through the fundamentals of Python, as well as advanced techniques in business analytics, with a focus on solving real-world business problems. In addition to the theoretical underpinnings of business analytics, the book is packed with hands-on examples, practical exercises, and case studies that demonstrate how these concepts are applied in real-world business scenarios. Whether you are trying to optimize marketing campaigns, improve sales forecasts, or understand customer behavior, the tools and techniques you will learn in this book will help you derive actionable insights from your data. Who Should Read This Book?This book is aimed at anyone interested in applying business analytics to solve real-world problems using Python. It is ideal for: Business Analysts: Who want to enhance their analytical skills and learn how to use Python for solving business problems.Data Scientists: Who are looking to expand their knowledge in business contexts and understand how to apply advanced analytics in a business environment.Managers and Decision Makers: Who want to understand how data-driven insights can inform strategic business decisions.Students and Beginners: Who are learning business analytics, data science, or related fields and want a practical guide to applying analytics using Python.This book is structured to cater to both beginners and more advanced users. Each chapter begins with a conceptual introduction to the topic, followed by practical, hands-on examples using Python. You will find step-by-step instructions, along with clear explanations of the code and the business implications of the results. Whether you are working through the chapters in order or focusing on specific topics, you will gain the skills necessary to apply business analytics in your organization. So, let's dive in and begin unlocking the true potential of your business data with Python! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Codice articolo 9798300531072

Titolo
Business Analytics using Python (Paperback)
Autore
Kumar P.
Editore
Independently Published
Anno di pubblicazione
2024
Condizione
new
Rilegatura
Paperback
Lingua
inglese
ISBN 13
9798300531072

Grand Eagle Retail

Bensenville, IL, U.S.A.

Venditore con 5 stelle

Venditore AbeBooks dal 12 ottobre 2005

Tariffe di spedizione nazionale per U.S.A.

ArticoloDa 6 a 14 giorni lavorativiDa 6 a 16 giorni lavorativi
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