A thorough and in-depth overview of data analysis with a focus of practical usage using industry-focused examples and accurate use cases.
This is an advanced textbook that provides a practical approach to data analytics, algorithms, and modeling techniques in a business setting.
One of the greatest strengths of this book is that it focuses on R through a lens of business problems rather than code. The book provides good explanation about the underlying issues, such as loan charge-off, risk analysis, and more.
A unique approach to Business Analytics with a focus on different application domains from External Environment Analytics to Supply Chain Analytics.
This text would provide for the opportunity to expand the skills of students and offer one a way to broaden the content covered in an advanced undergraduate course or first year graduate course. I think that the coverage of PCA and Text Analysis is particularly good and is becoming more and more mainstream. Thus, these are topics that need to be covered even at the undergraduate level but are difficult to fit into a single course. This text could provide the opportunity deal with that problem.
Good data analytics text using R that you can customize for program needs based upon discipline focus.
The book provides a business-specific, applied introduction to business analytics. It incorporates multiple business disciplines and perspectives so that students can understand ways that algorithms can be applied in business practice. The chapters are organized by application so that students can see multiple implementations of data science concepts.
This book is well-grounded in practical business decision making and includes straightforward discussion and interpretation of statistical output.
The content of this book is thorough, with each chapter including a case study and R code example.