Mahadi Hasan Miraz, Narishah Mohamed Salleh, Hwang Ha Jin

Python for Business Analytics (eBook, PDF)

Unlocking Data Insights for Strategic Decision-Making

• Format: PDF

Produktbeschreibung

This book provides a thorough introduction to Python, specifically designed for those in business analytics. It starts with the fundamentals of Python and gradually covers more advanced topics, including data manipulation, visualization, and analytics techniques. The content is structured to help readers build a strong foundation in Python, essential for success in data science and business analytics. The book also features real-world case studies and practical examples, demonstrating how Python can be applied in business decision-making. These insights make it a valuable resource for students and professionals who want to use Python to solve real business problems. Python's importance in today's data-driven industries cannot be overstated. Proficiency in this programming language enhances the ability to tackle complex challenges and supports strategic decision-making. For organizations, Python enables the setting of data-driven goals, improved performance, and the fostering of continuous learning. Its open-source nature and wide range of online resources make it accessible to everyone, ensuring that users are equipped with the skills needed in a rapidly evolving workplace. This book serves as a comprehensive guide for those aiming to excel in the field of business analytics through the effective use of Python.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 280
• Erscheinungstermin: 14. August 2025
• Englisch
• ISBN-13: 9789819682911
• Artikelnr.: 75201337

Autorenporträt

Dr. Mahadi Hasan Miraz is an associate professor at the School of Creative Industries, Astana IT University in Kazakhstan, and also serves as an assistant professor in the Department of Marketing and Entrepreneurship at Dhofar University, Oman. Previously, he was a lecturer in the Department of Digital Marketing at Curtin University Malaysia and held a position in the Department of Business Analytics at Sunway University, Malaysia. He has a strong background in research, having been involved in various national and international research grant projects, including a significant contribution to the FRGS government project. His research interests primarily focus on data-driven workplaces and the integration of artificial intelligence (AI) in business and marketing contexts. Dr. Miraz has published over 55 research papers in prestigious journals indexed by CABS, ABDC, WOS, and SCOPUS, garnering more than 1,050 citations.

Dr. Narishah Mohamed Salleh is a seasoned expert in enterprise systems, automation, and data analytics, blending over two decades of hands-on industrial experience with impactful academic contributions. With a PhD in Software Engineering from Universiti Kebangsaan Malaysia (UKM), she specializes in Requirement Engineering using hybrid elicitation techniques aligned with Lean Six Sigma methodologies. Her academic journey began with a B.Sc. in Electrical & Electronics Engineering from the University of Missouri-Columbia (USA) and a Master's in Manufacturing System Engineering from UTeM, Malacca, Malaysia. As a current faculty member in the Department of Business Analytics at Sunway University, Dr. Narishah has spearheaded the development of key modules such as ERP, MIS, Python, Power BI, BISD, Web Development and Visual Basic, aligning curriculum with real-world analytics and simulation-based learning environments. Her mentorship spans undergraduate to postgraduate levels, focusing on AI, RPA, and ERP system integration. She actively fosters innovation and industry collaboration-guiding students in real-world projects involving An Integrated of Web Development with RPA, machine learning, and deep learning. Her mission is to prepare future-ready graduates equipped with the mindset and skills to thrive in industrial collaborations and digital transformation ecosystems. She led award-winning digital transformation initiatives-developing intelligent automation systems, integrated financial supply chain solutions, and warehouse intelligence platforms to optimize incoming material tracking and reduce human dependence. Her leadership championed operational excellence through IR4.0 and business intelligence across global manufacturing domains.

Dr. Ha Jin Hwang is currently Professor and Director of School of Creative Industries, Astana IT University (AITU), Kazakhstan. Before joining AITU in January 2024, He served as Head and Professor of Information Systems at Department of Business Analytics, Sunway Business School, Sunway University (SU), Malaysia (2016-2023). Dr. Hwang worked at KIMEP University, Kazakhstan for six years (2010-2016), where he served as Dean of Bang College of Business (Feb. 2014-June 2016). He also served as Vice President of External Relations and Cooperation (2005-2009) and worked as Professor of Management Information Systems (1991-2010) for Catholic University of Daegu, Korea. Professor Ha Jin Hwang received MBA (1986) and DBA (1990) from Mississippi State University, U.S.A. He taught at Minnesota State University (Associate Professor of MIS, 1989-1991), Mankato, Minnesota, U.S.A. He served as President of Korea Association of Information Systems (2005) and President of Korea Internet Electronic Commerce Association (2008). His research interest includes AI in Education, Social Media Analytics, Logistics and Supply Chain Management, Internet of Things and its Applications, Emerging Technologies in Digital Transformation, etc.

Inhaltsangabe

Python for business analytics unlocking data insights for strategic decision making.- Basics of python programming.- Data manipulation with pandas.- Data visualization with matplotlib and seaborn.- Descriptive analytics.- Predictive analytics with scikit learn.- Advanced analytics and machine learning.- Case studies and real world applications.- Automating data analysis with python.- Best practices and future trends.- Outline of the study.- Pythons impact on ai and medicine.- Web based food recommendation.- Rate my stay.- Integration of ai and machine learning.- Automotive prices analytics.- Analytics for tour package recommendation system.