ISE Business Analytics

Business Analytics: Communicating with Numbers is a text that prepares students to understand, manage, and visualize data, apply tools, and communicate findings. It seamlessly threads topics of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics into a cohesive whole and includes features such as a synopsis and sample report to help students develop skills in articulating the business value of analytics from a non-technical standpoint.

Format: Paperback / softback
Length: 800 pages
Publication date: 08 March 2022
Publisher: McGraw-Hill Education

Business Analytics: Communicating with Numbers is a comprehensive textbook designed to equip students with the skills necessary to understand, manage, and visualize data, apply appropriate tools, and communicate findings and their relevance. Unlike other texts that merely repackage statistics and traditional operations research topics, this text seamlessly integrates the topics of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics into a cohesive narrative. It offers a holistic analytics process, encompassing the handling of real-life data that may be messy and/or small, while emphasizing the importance of effectively communicating findings through features such as a synopsis (a short writing sample) and a sample report (a longer writing sample) in every chapter. These features serve as valuable tools for students to develop their skills in articulating the business value of analytics by presenting insights from a non-technical perspective.

The textbook is organized into nine chapters, each focusing on a specific aspect of business analytics. The first chapter provides an introduction to the field and discusses the importance of data in decision-making. It introduces the basic concepts of data analysis, such as data collection, cleaning, and visualization, and explains how these tools can be used to extract insights from data.

The second chapter focuses on data wrangling, which involves extracting, cleaning, and transforming data to prepare it for analysis. It covers techniques such as data mining, data cleaning, and data transformation, and emphasizes the importance of ensuring data quality and accuracy.

The third chapter introduces descriptive analytics, which involves analyzing data to identify patterns, trends, and relationships. It covers techniques such as statistical analysis, data visualization, and hypothesis testing, and emphasizes the importance of interpreting findings in a business context.

The fourth chapter explores predictive analytics, which involves using statistical models and machine learning algorithms to make predictions about future events. It covers techniques such as regression analysis, time series analysis, and decision trees, and emphasizes the importance of identifying key drivers of business performance.

The fifth chapter focuses on prescriptive analytics, which involves using optimization algorithms and simulation techniques to identify the best possible decisions. It covers techniques such as linear programming, dynamic programming, and Monte Carlo simulation, and emphasizes the importance of considering constraints and uncertainties in decision-making.

The sixth chapter discusses the role.

The seventh chapter explores the role of data visualization in communicating findings and insights to stakeholders. It covers techniques such as data storytelling, data dashboards.

The eighth chapter discusses the ethical considerations and challenges associated with business analytics. It covers topics such as privacy, security, and bias, and emphasizes the importance of ethical decision-making and responsible data use.

The ninth chapter provides an overview of emerging trends and technologies in business analytics, such as big data, artificial intelligence, and machine learning. It covers the benefits and challenges of these technologies, and emphasizes the importance of staying up-to-date with the latest developments in the field.

Throughout the textbook, real-life examples and case studies are used to illustrate the practical applications of business analytics. These examples help students connect the theoretical concepts with practical situations and demonstrate the importance of analytics in driving business success.

In addition to the textbook, the authors have also developed a range of supplementary materials, such as online quizzes, quizzes, and exercises, to support students' learning and understanding of the topics covered. These materials are designed to reinforce the concepts presented in the textbook and provide additional practice opportunities for students.

Overall, Business Analytics: Communicating with Numbers is a comprehensive and engaging textbook that provides students with the skills and knowledge necessary to succeed in the field of business analytics. Its seamless integration of data wrangling, descriptive analytics, predictive analytics, and prescriptive analytics, combined with real-life examples and case studies, makes it an invaluable resource for anyone interested in gaining a deeper understanding of the power of data and its impact on business decision-making.

Weight: 1415g
ISBN-13: 9781265087685
Edition number: 2 ed