Business Analytics for Decision Making

Author

Vijayakumar P

Published

Jan 11, 2024

Welcome

Business Analytics for Decision Making is a comprehensive guide designed to equip readers with the essential skills and knowledge for applying business analytics in decision-making processes. This book seamlessly integrates theoretical concepts with practical applications, using MS Excel and two of the most powerful programming languages in the data science field: R and Python.

It covers a broad spectrum of data analytics. With an emphasis on data structures, statistical tests, data visualization techniques, and utilization of key packages from Python and R, this book is a practical resource for those looking to master business analytics for real-world applications.

Whether you’re a student stepping into the world of data science or a professional seeking to enhance your decision-making skills through data-driven insights, this book provides the tools and insights needed to navigate the complex landscape of business analytics.

About the Authors

Vijayakumar P is an accomplished educator and data professional with over eight years of teaching and research experience in business analytics, data science, and HR analytics. He is a UGC Junior Research Fellow (JRF) and has qualified the UGC NET and SET in Management multiple times, reflecting his strong academic foundation.

Proficient in Python, R, STATA, SPSS, AMOS, PLS-SEM, Tableau, Power BI, Google Looker Studio, GitHub, and Excel , he has guided students and professionals in transforming data into actionable insights. His teaching spans business analytics using R and Python, HR metrics and dashboards, business forecasting, and business research methods, and he has also developed interactive eBooks to enhance hands-on learning.

Vijayakumar’s work is marked by clarity, precision, and innovation—whether in research, classroom teaching, or applied analytics—making data more accessible, impactful, and meaningful for decision-making.

Inclusion of R & Python codes in this book

References

  • R for Everyone 🔗

  • Statistics for Management (Levin, Rubin) 🔗

  • Numerical Python Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib. Johansson, Robert. (2019). (2nd ed.). Apress.

  • Python for Data Analysis. Mckinney, Wes. (2013). O’Reilly.

Text Books

  • R in Action - Data Analysis and Graphics with R. Kabacoff, Robert. (2022). Manning Publications.
  • Practical Business Analytics Using R and Python. Hodeghatta, Umesh R., & Nayak, Umesh. (2023). Apress.
  • A Handbook of Statistical Analyses Using R. Everitt, Brian S., & Hothorn, Torsten. (2005).
  • Practical Statistics for Data Scientists. Bruce, Peter, Bruce, Andrew, & Gedeck, Peter. (2020). O’Reilly Media.