Data science and analytics have emerged as the most desired fields in driving business decisions. Using the techniques and methods of data science, decision makers can uncover hidden patterns in their data, develop algorithms and models that help improve processes and make key business decisions. Data science is a data driven decision making approach that uses several different areas and disciplines with a purpose of extracting insights and knowledge from structured and unstructured data. The algorithms and models of data science along with machine learning and predictive modeling are widely used in solving business problems and predicting future outcomes. This book combines the key concepts of data science and analytics to help you gain a practical understanding of these fields. The four different sections of the book are divided into chapters that explain the core of data science. Given the booming interest in data science, this book is timely and informative.

This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes. It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together. The first three chapters provide an introduction to BA, importance of analytics, types of BA-descriptive, predictive, and prescriptive-along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses on the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics-machine learning, neural networks, and artificial intelligence. The concluding chapter discusses on the current state, job outlook, and certifications in analytics.

Business Analytics: A Data-Driven Decision Making Approach for Business-Part I,/i> provides an overview of business analytics (BA), business intelligence (BI), and the role and importance of these in the modern business decision-making. The book discusses all these areas along with three main analytics categories: (1) descriptive, (2) predictive, and (3) prescriptive analytics with their tools and applications in business. This volume focuses on descriptive analytics that involves the use of descriptive and visual or graphical methods, numerical methods, as well as data analysis tools, big data applications, and the use of data dashboards to understand business performance. The highlights of this volume are: Business analytics at a glance; Business intelligence (BI), data analytics; Data, data types, descriptive analytics; Data visualization tools; Data visualization with big data; Descriptive analytics-numerical methods; Case analysis with computer applications.

The book is divided into three parts – (1) prerequisite to regression analysis followed by a discussion on simple regression, (2) multiple regression analysis with applications, and (3) regression and modeling including the second order models, nonlinear regression, and interaction models in regressions. All these sections provide examples with complete computer analysis and instructions commonly used in modeling and analyzing these problems. The book deals with detailed analysis and interpretation of computer results. This will help readers to appreciate the power of computer in applying regression models. The readers will find that the understanding of computer results is critical to implementing regression and modeling in real world situation. The book is written for juniors, seniors and graduate students in business, MBAs, professional MBAs, and working people in business and industry. Managers, practitioners, professionals, quality professionals, quality engineers, and anyone involved in data analysis, business analytics, and quality and six sigma will find the book to be a valuable resource.