Choose your book from the top business analytics books to read in 2021
If anyone wants to start the journey in business analytics to work with data analysis and data management efficiently and effectively, it is essential to search for books to broaden the mindset. It is important to gain sufficient knowledge and a clear understanding of the field with a large collection of books on business analytics. Yes, there are physical books as well as e-books on the Internet that may make you confused or overwhelmed. It is, indeed, difficult to select which business analytics books to refer to. But you have to start from the level of your understanding to have a clear picture of business analytics. Let’s explore some of the top business analytics books to read in 2021 to start the journey.
Top Business Analytics Books to Read in 2021
Business Analytics: The Science of Data-Driven Decision-Making
Author: U Dinesh Kumar
Business Analytics: The Science of Data-Driven Decision-Making is one of the top business analytics books in 2021 with 17 chapters on different components of analytics including predictive, descriptive, and prescriptive analytics. The readers can explore from the introduction to business analytics to statistical concepts and analytics techniques with different types of programming.
Business Analytics: 2nd Edition
Author: James Evans
Business Analytics 2nd edition elaborates the fundamental concepts of business analytics with a clear understanding of different tools on data analysis with real-life scenarios. This business analytics book consists of principles, how to communicate with analytics professionals as well as interpret analytic models for smarter decision-making processes. James Evans completed the teaching in four parts with a holistic approach from the view of descriptive, prescriptive, and predictive analysis.
Business Analytics: Applications to Consumer Marketing
Authors: Sandhya Kuruganti, Hindol Basu
Business Analytics: Applications to consumer marketing is one of the top books on business analytics that offers practical guidance on the application of analytics and data analysis to drive smart business decisions on consumer marketing. This book consists of strategic imperatives of analytics with a sharp focus on consumer marketing with real-life examples. The readers can gain sufficient knowledge of usage management, cross-sell retention management, quantitative methods, analytics ecosystem, and many more.
Business Intelligence Guidebook: From Data Integration to Analytics
Author: Rick Sherman
Business Intelligence Guidebook: From data integration to analytics is one of the top business analytics books that can guide anyone towards designing multiple business intelligence and data integration processes of an organization. The book will teach how to transform raw data into meaningful and in-depth business outcomes. The readers can design the overall architecture for functioning business intelligence systems with appropriate data analysis while supporting data warehousing. This business analytics book can provide readers with sufficient knowledge to drive success in this data-driven culture.
Business Intelligence, Analytics, and Data Science: A Managerial Perspective
Authors: Ramesh Sharda, Dursun Delen, and Efraim Turban
Business Intelligence, Analytics, and Data Science: A managerial perspective is one of the best business analytics books with a managerial approach to a clear understanding of business intelligence and its business analytics with data science. This book can be read by students who pursue courses on business intelligence or decision support systems. The content provides a solid foundation of business intelligence with hands-on practical examples, especially for aspiring business managers.
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python
Authors: Galit Shmueli, Peter C. Bruce, Peter Gedeck and Nitin R. Patel
Data Mining for Business Analytics: Concepts, techniques, and applications in Python provides detailed knowledge of the fundamental data mining techniques. The readers can gain a clear understanding of the use of Python for developing predictive models as well as techniques to seek patterns for data analysis. There are real-life practical examples to learn about key data mining methods with a focus on business analytics.
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