The Essential Guide to Data Science and its Applications

Description

The focus of this book is not on the mathematics or theory, but on the practical application. Formulas and equations will only be included when absolutely needed from a practitioner’s perspective. It is also not our aim to provide exhaustive coverage of all analytical techniques previously developed, but rather to cover the ones that really provide
added value in a business setting.

The book is written in a condensed, focused way because it is targeted at the business professional. A reader’s prerequisite knowledge should consist of some basic exposure to descriptive statistics (e.g., mean, standard deviation, correlation, confidence intervals, hypothesis testing), data handling (using, for example, Microsoft Excel, SQL, etc.), and data visualization (e.g., bar plots, pie charts, histograms, scatter plots).

Throughout the book, many examples of real‐life case studies will be included in areas such as risk management, fraud detection, customer relationship management, web analytics, and so forth. The author will also integrate both his research and consulting experience throughout the various chapters.

The book is aimed at senior data analysts, consultants, analytics practitioners, and PhD researchers starting to explore the field.